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Analysis of a Measure in Functional Cognition for Persons with Stroke

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Title:
Analysis of a Measure in Functional Cognition for Persons with Stroke
Physical Description:
1 online resource (127 p.)
Language:
english
Creator:
Berger, Kathleen A
Publisher:
University of Florida
Place of Publication:
Gainesville, Fla.
Publication Date:

Thesis/Dissertation Information

Degree:
Doctorate ( Ph.D.)
Degree Grantor:
University of Florida
Degree Disciplines:
Rehabilitation Science
Committee Chair:
Velozo, Craig A
Committee Members:
Marsiske, Michael
Bendixen, Roxanna Marie
Heaton, Shelley C

Subjects

Subjects / Keywords:
cognition -- functional -- measurement -- stroke
Rehabilitation Science -- Dissertations, Academic -- UF
Genre:
Rehabilitation Science thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract:
Stroke researchers increasingly recognize the affect of cognitive impairment on functional outcome for persons with stroke.  Yet, there is no measure that evaluates applied cognition in persons with stroke that incorporates both the secondary domains of cognition and the unique cognitive impairment observed in persons with stroke.  Through an extensive qualitative process, our research team developed an item bank for a measure of functional cognition in persons with stroke (MFC-S).  The overall purpose of this dissertation was to assess the measurement properties of the MFC-S. An item-level perspective was adopted in examining the: (1)dimensionality, (2) item level psychometrics and (3) the concurrent and predictive validity.  One hundred twenty-eight persons with stroke, stratified for chronicity and laterality of stroke, took a paper and pencil measure for the MFC-S.  A randomly selected subsample also took a battery of neuropsychological comparison measures. In the three studies of this dissertation it was ascertained that: (1) with an exploratory factor analysis, a ten-factor solution was defendable for the dimensionality of the MFC-S, and a principle components analysis of residuals supported essential unidimensionality for each of the ten domains, (2) acceptable to good psychometrics with nine out of ten domains separating persons into at least two distinct groups, and (3)  concurrent validity was supported by moderate to strong correlations with existing comparable measures but weak associations with more fundamental performance based measures.  Predictive validity was somewhat supported by predicting side of stroke in a profile analysis, but the language domain prediction was contrary to what we might have expected.  That is, persons with higher language ability were more likely to have had a left cerebral vascular accident.
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility:
by Kathleen A Berger.
Thesis:
Thesis (Ph.D.)--University of Florida, 2013.
Local:
Adviser: Velozo, Craig A.

Record Information

Source Institution:
UFRGP
Rights Management:
Applicable rights reserved.
Classification:
lcc - LD1780 2013
System ID:
UFE0045890:00001

MISSING IMAGE

Material Information

Title:
Analysis of a Measure in Functional Cognition for Persons with Stroke
Physical Description:
1 online resource (127 p.)
Language:
english
Creator:
Berger, Kathleen A
Publisher:
University of Florida
Place of Publication:
Gainesville, Fla.
Publication Date:

Thesis/Dissertation Information

Degree:
Doctorate ( Ph.D.)
Degree Grantor:
University of Florida
Degree Disciplines:
Rehabilitation Science
Committee Chair:
Velozo, Craig A
Committee Members:
Marsiske, Michael
Bendixen, Roxanna Marie
Heaton, Shelley C

Subjects

Subjects / Keywords:
cognition -- functional -- measurement -- stroke
Rehabilitation Science -- Dissertations, Academic -- UF
Genre:
Rehabilitation Science thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract:
Stroke researchers increasingly recognize the affect of cognitive impairment on functional outcome for persons with stroke.  Yet, there is no measure that evaluates applied cognition in persons with stroke that incorporates both the secondary domains of cognition and the unique cognitive impairment observed in persons with stroke.  Through an extensive qualitative process, our research team developed an item bank for a measure of functional cognition in persons with stroke (MFC-S).  The overall purpose of this dissertation was to assess the measurement properties of the MFC-S. An item-level perspective was adopted in examining the: (1)dimensionality, (2) item level psychometrics and (3) the concurrent and predictive validity.  One hundred twenty-eight persons with stroke, stratified for chronicity and laterality of stroke, took a paper and pencil measure for the MFC-S.  A randomly selected subsample also took a battery of neuropsychological comparison measures. In the three studies of this dissertation it was ascertained that: (1) with an exploratory factor analysis, a ten-factor solution was defendable for the dimensionality of the MFC-S, and a principle components analysis of residuals supported essential unidimensionality for each of the ten domains, (2) acceptable to good psychometrics with nine out of ten domains separating persons into at least two distinct groups, and (3)  concurrent validity was supported by moderate to strong correlations with existing comparable measures but weak associations with more fundamental performance based measures.  Predictive validity was somewhat supported by predicting side of stroke in a profile analysis, but the language domain prediction was contrary to what we might have expected.  That is, persons with higher language ability were more likely to have had a left cerebral vascular accident.
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility:
by Kathleen A Berger.
Thesis:
Thesis (Ph.D.)--University of Florida, 2013.
Local:
Adviser: Velozo, Craig A.

Record Information

Source Institution:
UFRGP
Rights Management:
Applicable rights reserved.
Classification:
lcc - LD1780 2013
System ID:
UFE0045890:00001


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1 ANALYSIS OF A MEASUR E OF FUNCTIONAL COGN ITION FOR PERSONS WI TH STROKE By KATHLEEN ANN BERGER A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2013

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2 2013 Kathleen Ann Berger

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3 To my mom and dad

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4 ACKNOWLEDGEMENTS There are many, many people who have supported me through the graduate school journey. First I would like recognize my chair and mentor, Craig Velozo for introducing me to Rasch analysis and maintaining a sense of calm when I really needed it. He teaches by example, with integrity and a very strong work ethic. I am very lucky to have had him as a mentor. Thank you, Dr. Velozo. Next, I would like to thank my committee members: Roxanna Bendixen, Shelley Heaton and Michael Marsiske for their expertise an d support. Thanks to Roxanna for her insights and support through the writing process. Roxanna was always willing to lend an ear. Shelley Heaton for her help navigating the world of neuropsycholgocial assessment and her willingness to scan some much nee ded documents for me. To Michael Mariske who taught me through three great statistics courses. I have really appreciated his humor and his willingness to serve on my committee among the gazillion he serves on. It has served me well. Beyond my academic support system, I need to recognize my family, friends and colleagues at Kris' Camp. Thanks to Michelle Welde Hardy whose energy, integrity and confidence in our work has fed my journey. Also, to the many therapists, coworkers and families who have simil arly shared in my passion. It has truly been a group effort. Lastly, thanks to Kris, Chelsea and Kevy who have been a huge source of inspiration, support and encouragement.

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5 TABLE OF CONTENTS Page ACKNOWLEDGEMENTS ................................ ................................ ............................... 4 LIST OF TABLES ................................ ................................ ................................ ............ 8 LIST OF FIGURE S ................................ ................................ ................................ .......... 9 LIST OF ABBREVIATIONS ................................ ................................ ........................... 10 ABSTRACT ................................ ................................ ................................ ................... 11 CHAPTER 1 ANALSYIS OF A MEASURE OF FUNCTIONAL COGNITION FOR PERSONS WITH STROKE ................................ ................................ ................................ ....... 13 1.1 Classical Test Theory ................................ ................................ ....................... 14 1.2 Modern Test Theory ................................ ................................ .......................... 16 1.3 Value added benefit of MTT ................................ ................................ .............. 18 1.3.1 1) Difficulty with comparison across different assessments of a similar construct ................................ ................................ ................... 18 1.3.2 2) Long tests that may contain redundant items ................................ .. 19 1.3.3 3) Assessments that are sample and item dependent ......................... 20 1.3.4 4) Assessments that do not achieve the objective measurement principle of equal interval scaling. ................................ ........................ 22 1.4 IRT informing theory and practice: ................................ ................................ .... 23 1.5 Conclusion ................................ ................................ ................................ ........ 24 2 A MEASURE OF FUNCTIONAL COGNITION OF STROKE: ASSESSING DIMENSIONALITY ................................ ................................ ................................ 27 2.1 Methods ................................ ................................ ................................ ............ 30 2.1.1 Instrumentation ................................ ................................ .................... 30 2.1.2 Participants ................................ ................................ .......................... 31 2.2 Data A nalysis ................................ ................................ ................................ .... 32 2.2.1 Unidimensionality ................................ ................................ ................. 32 2.2.2 Subject to item ratio and item parceling ................................ ............... 33 2.2.3 Dimensionality Analysis ................................ ................................ ....... 33 2.3 Results ................................ ................................ ................................ .............. 34 2.3.1 Exploratory Factor Analysis ................................ ................................ 34 2.3.2 Principle Components Analysis on Residuals ................................ ...... 36 2.4 Discussion ................................ ................................ ................................ ........ 37 2.5 Conclusion ................................ ................................ ................................ ........ 3 9 3 MEASURE OF FUNCTIONAL COGNITION IN STROKE: RASCH ANALYSIS ...... 44

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6 3.1 Methods ................................ ................................ ................................ ............ 45 3.1.1 Participants ................................ ................................ .......................... 45 3.1.2 Instrumentation ................................ ................................ .................... 46 3.2 Ad ministration procedures ................................ ................................ ................ 47 3.3 Data analysis ................................ ................................ ................................ .... 47 3.3.1 Unidimensionality ................................ ................................ ................. 47 3.3. 2 Rasch Analysis ................................ ................................ .................... 48 3.4 Results ................................ ................................ ................................ .............. 49 3.4.1 Language ................................ ................................ ............................. 50 3.4.2 Item Person Map ................................ ................................ ................. 50 3.4.3 Reading & Writing ................................ ................................ ................ 51 3.4.4 Item Person Map ................................ ................................ ................. 51 3.4.5 Numerical Calculation ................................ ................................ .......... 51 3.4.6 Item Person Map ................................ ................................ ................. 51 3.4.7 Limb Praxis ................................ ................................ .......................... 52 3.4.8 Item Person Map ................................ ................................ ................. 52 3.4.9 Visuospatial ................................ ................................ ......................... 52 3.4.10 Item Person Map ................................ ................................ ................. 53 3.4.11 Social Use of Language ................................ ................................ ....... 53 3.4.12 Item Person Map ................................ ................................ ................. 54 3.4.13 Emotional Function ................................ ................................ .............. 54 3.4.14 Item Person Map ................................ ................................ ................. 54 3.4.15 Attention ................................ ................................ ............................... 55 3.4.16 Item Person Map ................................ ................................ ................. 55 3.4.17 Executive Function ................................ ................................ .............. 55 3.4.18 Item Person Map ................................ ................................ ................. 56 3.4.19 Memory ................................ ................................ ................................ 56 3.4.20 Item Person Map ................................ ................................ ................. 56 3.4.21 Person misfit ................................ ................................ ........................ 57 3.5 Disc ussion ................................ ................................ ................................ ........ 57 3.5.1 Item Misfit ................................ ................................ ............................ 58 3.5.2 Person Misfit ................................ ................................ ........................ 59 3.5.3 Co nclusion ................................ ................................ ........................... 60 4 A VALIDITY STUDY OF A MEASURE OF FUNCTIONAL COGNITION FOR PERSONS WITH STROKE ................................ ................................ .................... 75 4.1 Methods ................................ ................................ ................................ ............ 76 4.1.1 Participan ts ................................ ................................ .......................... 76 4.1.2 Instrumentation ................................ ................................ .................... 77 4.1.2.1 The MFC S ................................ ................................ ........... 77 4.1.2.2 Repeatable Battery for the Assessment of Neuropsychological Status (RB ANS) 72 ................................ 77 4.1.2.3 Digit Symbol Coding ................................ ............................. 78 4.1.2.4 Behavior Rating Inventory of Executive Functions Adult (BRIEF) ................................ ................................ ................ 78

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7 4.1.2.5 Functional Assessment of Communication Skills for Adults (ASHA FACS) 30 ................................ ................................ .... 79 4.1.2.6 Center for Epidemiologic Studies Depression Sc ale (CES D) ................................ ................................ ................ 79 4.1.2.7 Wechsler Individual Achievement Tests (WIAT II) 79 ............. 79 4.1.2.8 Trails A & B ................................ ................................ ........... 79 4.1.2.9 Delis Kaplan Executive F unctions Scale (D KEFS) Sorting Test 20 ................................ ................................ .................... 80 4.1.2.10 Mini Florida Apraxia Battery (Mini FAB) ............................. 80 4.1.3 Administration Procedure ................................ ................................ ..... 81 4.1.4 Data Analysis ................................ ................................ ....................... 81 4.2 Results ................................ ................................ ................................ .............. 82 4.2.1 Correlation with concurrent measures ................................ ................. 82 4.2.2 Profile Analysis ................................ ................................ .................... 82 4.2.3 Logistic regression ................................ ................................ ............... 83 4.3 Discussion ................................ ................................ ................................ ........ 83 4.4 Conclusion ................................ ................................ ................................ ........ 85 5 SUMMARY AND CONCLUSION ................................ ................................ ............ 95 5.1 Summary ................................ ................................ ................................ .......... 95 5.2 Conclusion ................................ ................................ ................................ ........ 97 APPENDIX A PARTICIPANT CHARACTERISTICS ................................ ................................ ..... 99 B PATTERN MATRIX RETAI NING FOUR FACTORS ................................ ............. 101 C PATTERN MATRIX RETAI NING FIVE FACTORS ................................ ............... 102 D SECONDARY DIMENSION AFTER REMOVING PRIMA RY RASCH DIMENSION ................................ ................................ ................................ ......... 103 E MFC STROKE PAPER AND PEN CIL FIELD TEST ITEM POOL F OR PATIENT 106 LIST OF REFERENCES ................................ ................................ ............................. 120 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 127

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8 LIST OF TABLES Table Page 2 1 Pattern matrix for 10 factor solution ................................ ................................ .... 41 2 2 ................................ ................................ ........................ 42 2 3 Summary of PCA of standardized residuals ................................ ....................... 43 3 1 Summary of Rasch psychometrics for MFC S ................................ .................... 61 3 2 Misfitting person demographics ................................ ................................ .......... 63 3 3 Reverse coding items ................................ ................................ ......................... 64 4 1 Participant characteristics ................................ ................................ ................... 86 4 2 Neuropsychological measures and associated MFC S domain ......................... 89 4 3 MFC S Domain correlations with neuropsychological measures ........................ 90 4 4 Regression coefficients for binary logistic model predicting left or right CVA ..... 92 4 5 Model classification of right or left CVA ................................ .............................. 93

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9 LIST OF FIGURES Figure Page 1 1 Two item characteristic curves with differing item discrimination ........................ 25 1 2 Interval and ordinal scale examples ................................ ................................ ... 26 1 3 Item characteristic curve ................................ ................................ ..................... 26 3 1 Language person item map ................................ ................................ ................ 65 3 2 Reading and writing person item map ................................ ................................ 66 3 3 Numerical calculation person item map ................................ .............................. 67 3 4 Limb praxis person item map ................................ ................................ .............. 68 3 5 Visuospatial person item map ................................ ................................ ............. 69 3 6 Social language person item map ................................ ................................ ...... 70 3 7 Emotional function person item map ................................ ................................ .. 71 3 8 Attention person item map ................................ ................................ .................. 72 3 9 Executive function person item map ................................ ................................ ... 73 3 10 Memory person item map ................................ ................................ ................... 74 4 1 Left vs. right comparison profile ................................ ................................ .......... 94

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10 LIST OF ABBREVIATIONS ACS Applied Cognition Scale CTT Classical Test Theory CVA Cerebral Vascular Accident FIM Functional Independence Measure ICC Item Characteristic Curve IRT Item Response Theory LSAT L AW S CHOOL A CHIEVEMENT TEST MFC S A Measure of Functional Cognition for Persons with Stroke MTT Modern Test Theory RBMT Rivermead Behavioral Memory Test

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11 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy ANALYSIS OF A MEASUR E OF FUNCTIONAL COGN ITION FOR PERSONS WI TH STROKE By Kathleen Ann Berger August 2013 Chair: Craig Velozo Major: Rehabilitation Science Stroke researchers increasingly recognize the affect of cognitive impairment on functional outcome for persons with stroke. Yet, there is no measure that evaluates applied cognition in persons with stroke that incorporates b oth the secondary domains of cognition and the unique cognitive impairment observed in persons with stroke. Through an extensive qualitative process, our research team developed an item bank for a measure of functional cognition in persons with stroke (MF C S). The overall purpose of this dissertation was to assess the measurement properties of the MFC S. An item level perspective was adopted in examining the: (1) dimensionality, (2) item level psychometrics and (3) the concurrent and predictive validity One hundred twenty eight persons with stroke, stratified for chronicity and laterality of stroke, took a paper and pencil measure for the MFC S. A randomly selected subsample also took a battery of neuropsychological comparison measures. In the three studies of this dissertation it was ascertained that: (1) with an exploratory factor analysis, a ten factor solution was defendable for the dimensionality of the MFC S, and a principle components analysis of residuals supported essential unidimensionality for each of the ten domains, (2) acceptable to good psychometrics

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12 with nine out of ten domains separating persons into at least two distinct groups, and (3) concurrent validity was supported by moderate to strong correlations with existing comparable meas ures but weak associations with more fundamental performance based measures. Predictive validity was somewhat supported by predicting side of stroke in a profile analysis, but the language domain prediction was contrary to what we might have expected. Th at is, persons with higher language ability were more likely to have had a left cerebral vascular accident.

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13 CHAPTER 1 ANALSYIS OF A MEASURE OF FUNCTIONAL COGNITION FOR PERSONS WITH STROKE In order to move rehabilitation science forward and evaluate therapeutic interventions, investigators need to be able to compare outcomes between studies, facilities and therapists. Yet, although rehabilitation clinicians are encouraged,, 48, 76 even require d, to use standardized outcome measures when evaluating clients, the number of clinicians who use standardized measures are limited. 41 In addition to lack of assessment. Further, while clinicians agree that standardized assessments are important to administrative and payor decisions, they rarely inform immediate treatment decisions. 84 For example, the Functional Independence Measure (FIMTM) 44 is an assessment currently used on admission and discharge at many rehabilitation settings to evaluate functional independence. Yet, obtaining a score on the moto r portion of the FIM will not inform the clinician beyond the qualitative judgment that she requires minimal assistance for grooming. Assessments that are informative and efficient would facilitate use by clinicians. In fact, some health outcomes investi gators cite advantages in efficiently informing therapeutic treatment plans as an asset of measures created using modern test theory (MTT) procedures. 84 Measure development procedures currently fall into two c ategories classical test theory (CTT), and modern test theory (MTT). While many currently available assessments have been developed using CTT, many health outcomes researchers have turned to modern test theory (MTT) procedures to optimize scale developm ent. 83 Two primary advantages to using MTT developed assessments include: optimized ability to compare scores across studies, facilities and therapists; and improved ability to

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14 inform theory development. For examp le, many assessments available to clinicians and researchers were created using CTT, 21 which use standardization to compare persons. However, scores from standardized assessments cannot be easily compared across studies as standardized scores are sample and test dependent. Scales developed with MTT address concerns of study comparison and are considered sample and test independent. This paper reviews key concepts of classical and modern test theory, emphasizing the val ue added benefit of MTT. More specifically, MTT investigators cite improved efficiency, equal interval measurement and theory development as key advantages of MTT developed measures. 92 1.1 Classical Test Theory CTT encompasses a set of concepts and statistical procedures that are the foundation for numerous assessment tools. Classical test theory proposes that a measured constr uct, and measurement error, represented in the equation: X 1 = T X + E 1 (1 1) Where X 1 is the observed score on an assessment, which is the sum of the true score and the error associated with the measure. Error may include things such as noise in the envi ronment, misunderstanding a question or variance in the manner a person administers a test. Assessments developed using CTT focus on reducing the measurement error, so that the observed score approximates the true score as close as possible. The primary challenge in CTT is that the true score is unobservable. DeVellis (2006) summarizes CTT assumptions that address this: 1) the set of items comprising

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15 an assessment should represent one construct; 2) items should equivalently represent the construct; and 3) items that highly correlate with each other are thought discriminate better on the given construct. Though this suggests that CTT focuses on item properties, in practice CTT focuses on scale properties. That is, how well does a set of items represent a true score? To resolve this, CTT assumes items are strictly parallel. That is, that the set of items are unidimensional; they represent one underlying construct. Additionally, each item covaries equivalently with the construct. Put differently, each item is an equally good indicator of the construct. Then, if the error associated with an item is common association with the underlying construct. This association is cal led reliability. Though these assumptions are strict, and thus unrealistic, other models exist that relax these assumptions but support estimation of scale reliability with item correlation. 6 5 y, and increases as includes the number of items in a scale as well as the correlations of th ese items. But, because it is often easier to increase the number of items than increase the correlation of items, the easiest way to increase scale reliability is to increase the items, increasing test length. Advantages of using CTT include: 1) familiar ity to investigators, 2) easy access to statistical packages needed to perform the procedures such as calculating

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16 variety of items that represent a construct, can attenuate err ors associated with one particular item. However, disadvantages include: 1) difficulty with comparison across different assessments of a similar construct; 2) long tests that may contain redundant items; 3) assessments that are sample and item dependent; and 4) assessments that do not achieve the objective measurement principle of equal interval scaling. These challenges and how MTT addresses them are detailed below. 1.2 Modern Test Theory Rehabilitation outcomes researchers increasingly use modern test theory methods to create measurement scales. 14, 83 Item response theory (IRT), the statistical analysis procedures used in MTT, focuses on item level statistics, in contrast with CTT focus on scale level psychometrics. IRT scales, similar to CTT scales, assume unidimensionality. MTT developers suggest the inclusion of easy items and hard items, 61 representing the breadth of a construct. For exampl e, in a test for fear of falling in the elderly, Velozo and Peterson (2001) 82 In t his manner, items used represent a range of a trait. Person ability is measured based on how a per son responds to an item. On a fear of falling scale, a person who has high fear would be more likely to report feeling fearful when getting out of bed as c ompared to someone with little fear of falling. Further, while all IRT models estimate item difficulty, two parameter models also estimate item discrimination and three parameter models add an estimate of guessing. Person ability for the construct is meas ured according to the response on an item and how difficult that item is or how well the item discriminates on the latent trait. For example, a person who has a higher level of ability would be more likely to pass a more

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17 difficult item. Figure 1 1, below presents two items with differing discrimination parameters. The slope at the level of item difficulty represents the item discrimination parameter. Items with steeper slopes discriminate persons better on the measured trait. Many rehabilitation resear ch investigators use the one parameter model, also response to an item is a function of person ability and item difficulty. Scale measures are log transformed and converted to logits (log odds units), which is an interval scale. 8 Rasch model proponents propose that equal interval measures are a key advantage of the Rasch model. The equal interval property of the one parameter IRT model is lost w ith further parameter estimation. 91 Equal intervals allow for arithmetic functions such as addition and subtraction. Thus, as shown in figure 1 Alternatively, or dinal scale steps are not equivalent which makes it more difficult to interpret if an investigator seeks to determine health care intervention efficacy. For example, looking at the ordinal scale below, a person improving from 1 to a 2 would improve more t han a person improving from 2 to 3. Yet, measuring on the ordinal scale, each person would improve one unit. Alternatively, using the interval scale, a person improving from 1 to a 2 would improve equivalently to a person improving from 2 to 3. Also, a person improving two units demonstrates 2 times the improvement of a person improving 1 unit. The item characteristic curve (ICC), shown in figure 1 3 below, illustrates the core concept of IRT

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18 discrimination. The probability that a person passes an item increases as they have a higher amount of ability. Though CTT and MTT both assume that created outcomes assessment measure one primary construct, the procedures used in MTT address measurement challenges seen in CTT measures. Below, we discuss how IRT analyses address four challenges of CTT. Lastly, we describe how IRT measures have i nformed theory and practice in upper extremity stroke rehabilitation. 1.3 Value added benefit of MTT 1.3.1 1) Difficulty with comparison across different assessments of a similar construct CTT measures typically produce a score. For example, the FIM 44 produces a score of 18 to 126 based on ratings of assistance needed to perform eighteen functional motor and cognitive tasks, (bathing, grooming or memory, e.g.). Similar to the cognitive portion of the FIM, the Rivermead Behavi oral Memory Test (RBMT) 89 contains items to assess functional memory. However, though these tests provide norms and standardized scores for comparison, these scores are sample dependent, which makes it challenging to compare across groups and studies. Standardization is dependent on sample heterogeneity and thus can change between samples. Though procedures do exist that could allow for comparison between scores obtained on instruments developed using CTT such as effect size, 43 MTT procedures make these comparisons in a more straightforward manner. Specifically, IRT linking procedures put different measurement scales on a common metric, 17, 34, 81 and MTT measures possess sample and item free properties. A more detailed explanation of the

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19 property of sample and item independence is addressed in the sample and test free property of MTT b elow. 1.3.2 2) Long tests that may contain redundant items One way CTT increases the precision of measures is by adding items. 21 In CTT errors associated with items are assumed random, errors can affect a score in either dire ction and thus cancel each other out, with a mean of zero. The law of large numbers theorem demonstrates that, for a random distribution, as the number of variables or items increases, the sample mean approaches the true mean. Increased items then decreas es the error associated with a score, as the sample error approaches the true population mean of zero. However, adding items also increase the time needed to complete the test, and redundant items may create superficial precision. Alternatively, instrum ents developed with MTT do not need all items to determine higher probability of passing a more difficult item. If a person passes an item at the middle of the scale, presenting items at the lower end of the scale is unnecessary. Further, many measures assess a need, or a diagnosis and have a cutoff score. For those persons extreme on the scale, only a few items might be needed to ascertain that at the extreme low or high part of a scale. They either do or do not meet a certain cutoff. For example, the Berg Balance Scale 5 measures functional balance ability. Persons scoring less than a 45 have been found to be at risk for falling. Using MTT, a person passing the higher items of standing on one foot or standing with one foot out in front, would not need to pass the easier items, such as standing unsupported.

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20 For persons extreme on the scale, acceptable m easurement error could be greater than the case where a person falls in the middle ability level, closer to a cutoff score. To evaluate a middle level person, one may want more items and a greater precision, less measurement error. The ideal item is one where the odds are even that a person passes or fails it. Velozo and colleagues proposed an item hierarchy order for fear of falling. 81 For someone who is afraid of falling getting in and out of bed, or on or of f the toilet, further items are unnecessary to obtain a measure. We can use just that part of the scale. On the other hand, for someone falling closer to the middle of the scale, more items will help refine exactly where that person falls on the scale. Summarizing, because MTT relies on item level psychometrics and the ICC, instruments developed using MTT can vary in test length. All of the items are not needed to obtain a person score. However, the more items used will decrease measurement error, if needed. 1.3.3 3) Assessments that are sample and item dependent MTT proposes that instruments developed using these procedures are sample and test free. When measures remain stable with different instruments that evaluate a similar construct, objective measurem ent is attained. 91 Objective measurement requires two components: 1) the calibrations used in an instrument need to be independent of the items or objects used to calibrate it, and 2) the measurement of the items or obje cts needs to be independent of the instrument that is used to measure them. To illustrate how a measure should be item and sample free, Wright (1968) uses the example of measureme nt error, depending on using a yardstick or a tape measure. In turn, the tape measure or yardstick does not change based on which person is being measured.

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21 Alternatively, measures created using CTT are dependent on the sample and items. For example, sta ndardized test scores are dependent on the sample that takes the test. For example, an IQ assessment would score a person at a different percentile rank depending on the comparison group. If compared to high school seniors, the score might be in the 90th percentile. If compared to college seniors, the same score might comparison group. To illustrate how MTT procedures develop instruments that are independent of the sample us ed, Wright (1968) compares instrument development using CTT and MTT. First, he splits a sample of law student scores on the verbal portion of the LSAT into two groups. One group performed best on a test while the second group performed worst. The range of scores in the lowest performing group is 10 23; the range of scores in the higher performing group is 33 46. In a graph, Wright (1968) demonstrates that person calibrations for each group using CTT instrument development form two distinct lines. One c an see that an instrument developed using either sample does not allow for range. Th ough this example is certainly exaggerated, it also provides for a clear test of the sample free property proposed by MTT procedures. Because the calibration methods are based on how a person would fair when presented with any given item, abilities can be estimated using either range of scores, and for persons at any point in the range of possible test scores. This can be done because the estimation of ability is

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22 based on what the probability is that a person with a certain amount of ability would an item, given its difficulty level. That is, a person with a high ability level would be more likely to pass a more difficult item. Moreover, comparing calibrations based on the two groups, the person ability calibrations are almost identical when MTT calibration is used. In other words, a measure created using MTT calibration procedures is sample free. While the above discussion addresses how MTT calibrations crea te measures that are independent of the sample, MTT also proposes that the instruments are test free. That is, they are not dependent on the specific items used to create the measure. Using the same law student sample, to illustrate test independence, in MTT, Wright (1968) splits the test questions into two groups: one made up of the easier items and one made up of the harder items. If person ability measures developed using MTT procedures are statistically equivalent, the mean of the standardized diff erence should be 0, with a standard deviation of 1. Examining the second part of Table 1 1, where the log ability transformations are noted, we can see that the difference in ability measures for a person on the two different tests are essentially 0 (.003 ), with a standard deviation of 1 (1.014). 1.3.4 4) Assessments that do not achieve the objective measurement principle of equal interval scaling. The Rasch, or one parameter IRT model, produces measures with equal intervals. To illustrate this, I use the Ber g Balance Scale, 5 a scale used by physical therapists to assess balance. On the Berg Balance Scale, persons scoring below a 45

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23 are at risks for falls. Yet, what we cannot tell from this scale is whether the differen ce between 35 and 40 is the same as the difference between 40 and 45. This is an ordinal scale, as shown in Figure 1 2. Thus, we cannot easily compare if two persons showing an improvement of 5 points exhibited equivalent improvement. Alternatively, a 5 unit comparison on a Rasch interval scale would be equivalent. 1.4 IRT informing theory and practice: Beyond measurement benefits, rehabilitation scientists have proposed that IRT analysis can inform rehabilitation theory and practice. For example Woodbury et al. 2007, found that persons with stroke did not recover in a proximal to distal pattern as had long been theorized. Rather, they recovered in a simple to complex movement pattern. Also, it should be noted that this was done using IRT procedures with a measure that was created using CTT. Occupational and physical therapy intervention in persons with stroke have assumed that recovery following stroke follows a proximal to distal direction, similar to typical development. But, when persons with stroke wer e evaluated using the FMA for the upper extremity, with the items evaluated using IRT procedures, Woodbury et al. 2007 showed using Rasch generated item difficulty hierarchies that recovery proceeding from simple to complex movements better explained upper extremity stroke recovery, rather than a proximal to distal pattern. 90 Further, Woodbury and colleagues suggest that clinicians can better identify the Rasch generated form, the keyform displays items in a difficulty hierarchy format. Identifying where a person falls on the keyform allows the clinician to quickly ascertain

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24 which items fall near the client ability level Thus, allowing for efficient goal setting for short and long term goals. 1.5 Conclusion This paper details the value added benefit of using MTT procedures when creating health outcome measures. As health outcomes research moves forward, MTT procedures aid in comparing outcomes between studies, facilities and therapists. Additionally, MTT provides a framework for evaluating theory and practice. This should not be seen as pitting CTT against MTT, rather, that MTT allows for new means to further rehabilitati on research. As illustrated by Woodbury & Velozo (2007 ), 90 using MTT procedures on a sound CTT measure furthered understanding of recovery in upper extremity function following stroke.

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25 Figure 1 1 Two item characteristic curves with differing item discrimination

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26 Figure 1 2 Interval and ordinal scale examples Figure 1 3 Item characteristic curve

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27 CHAPTER 2 A MEASURE OF FUNCTIONAL COGNITION OF STROKE: ASSESSING DIMENSIONALITY In order to better understand the functional impact of cognitive change due to aging, disease and rehabilitation, researchers have focused on measures of everyday ability. 2, 17, 44, 46, 74, 89 Two examples of applied cognition measures used or developed with persons with stroke include the Functional Independence Mea sure (FIM) 44 and a more recently developed measure, the Applied Cognition Scale (ACS). 17 Though the FIM has been used extensively in rehab settings, the range is limited. The FIM includes five general cognitive items: Cognitive comprehension, Expression, Social interaction, Problem solving and Memory. These items are rated on a seven point ordinal scale that ranges from complete dependence to complete independence. In an ef fort to improve measurement of applied cognition, Coster and colleagues 17 developed an applied cognition scale. Though the 46 item ACS improves the measurement breadth of functional cognition, included items do not distinguish between separate cognitive constructs. ACS developers included functional cognition items from seven existing measures. Examinees rated items for degree of difficulty. Example items include: (1) carrying a conversation with a friend in a no isy place, and (2) asking someone to do something for you. The items were generic in that they did not include items specific to a particular disease, and did not differentiate between cognitive domains. Persons affected by stroke present with a unique co gnitive profile. 9 Further, while cognitive research evidences a strong general factor of cognition, decades of cognitive research evidences that the general factor encompasses many subdomains. 10 12, 39, 62 As such, our research team

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28 developed a measure of functional cognition in persons with stroke (MFC S). More specifically, the aim in developing the MFC S was to provide clinicians with a measure of applied cognition that included cognitive subdomains most pertinent to persons with stroke. We defined functional cognition as the ability to perform everyday activ ities that rely heavily on cognition, and separated functional cognition items into 10 cognitive domains: Language, Reading & Writing, Numerical Calculation, Visuospatial, Limb Praxis, Social Language, Emotional Function, Attention, Executive Function and Learning & Memory. 23 The qualitative process that developed these domains is described in detail in Donovan et al, 2008 23 MTT methods, as well as most psychometrics, requi re that a measure is unidimensional. 56 other factors. While perfect unidimensionality i s ideal, what a test developer investigates is if the measure is essentially unidimensional. Linacre (2009) 53 suggests that when evaluating dimensionality, the measurement developer considers the purpose of the meas ure. Many constructs we may want to measure may contain more than one dimension. For example, a test for arithmetic may include addition and subtraction items. We would not want to separate these into two separate measures if the intent is to measure ge neral math ability. When evaluating unidimensionality for the ten domains of the MFC S, we expect that there will be some evidence of secondary dimensions.

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29 Each of the MFC S domains included items from different constructs that fall under a broader cons truct, the intended measurement construct. For example, the language domain contains some items that represent expressive speech and some items that represent receptive speech. However, the intent is to measure functional language ability. In cases wher e there is evidence of secondary dimensions, Linacre suggests inclusion of an equivalent amount of items on the secondary dimensions when developing the final measure. 53 A variety of statistical methods, discussed further below and in the methods section, allow investigators to examine underlying dimensions of a measure and evaluate evidence of multidimensionality. 32, 56 In this study, we first explore the und erlying factor structure of the entire MFC S to evaluate quantitatively whether it is justifiable to include these 10 domains under the broader umbrella of functional cognition. Next, we investigated whether it is justifiable that each of the 10 domains o f the MFC S measure their intended construct. Alternatively, we investigated whether there was evidence that items in a given domain should be split into two separate measures. Relevant to investigation of the entire measure factor structure, though ext ensive qualitative work went into the development of the MFC S, we are unaware of prior factor analysis work supporting a strong apriori factor structure hypothesis specific to functional cognition in persons with stroke. However, there is a large body of work that has examined the factor structure of cognition more broadly. For example, Spearman 78 originally proposed the presence of a 'g' factor to explain the high correlation between individual performance on different

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30 tests of mental ability. Since that time, investigators have developed and expanded on this theory. As cognition is thought to include a higher order general factor, encompassing several subdomains, 1 0, 62 we expect evidence for a higher order general factor of functional cognition. Several methods exist to establish unidimensionality. 32, 56, 73 Historically, methods used to evaluate dimensionality include factor analysis, 32, 73 principal components analysis (PCA), 56 and item response theory fit sta tistics 1 There are strong arguments supporting each of these approaches. In order to evaluate dimensionality, but restricted by sample size, we chose to perform an exploratory factor analysis followed by a PCA o f the standardized residuals. Specifically, this study attempted to answer two questions: (1) Is there evidence to support a ten factor solution as an adequate fit for the MFC S? and (2) For each of the ten proposed domains within the MFC S, does the evi dence support unidimensionality? 2.1 Methods 2.1.1 Instrumentation The instrument development process 23 proceeded in four phases: (1) a literature review, (2) input from an expert advisory panel, (3) item development and (4) a field test. Donovan et al. 2008, detail the approach in conceptualizing functional cognition in stroke. Initially, the literature review produced seventeen constructs. An additional construct, apraxia was added after feedback from the advisory panel, resulting in ten final domains for the MFC S. Initial item development within each of ten domains was guided by Rasch measurement principles, neuropsychological theory and literature review. A

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31 in each domain. The initi al item pool contained 266 items. These 266 items were then presented to focus groups of persons with stroke, acute (N=20) and chronic (N=20), their significant others/caregivers and healthcare professionals. Detailed methods and results of the focus grou p are currently in a manuscript under preparation. Based on the focus groups items were removed, modified and added resulting in a final item bank of 244 items. The finalized 244 items crossed ten subdomains (language 12 items, reading/writing 14 item s, numeric calculation 9 items, limb praxis 10 items, visuospatial function 31 items, social use of language 32 items, emotional function 40 items, attention 25 items, executive function 41 items, memory 29 items). 2.1.2 Participants Approval f or this study was obtained through the IRB 01 at the University of Florida. Each participant signed an informed consent approved by the IRB. Participants were recruited at local rehabilitation hospitals, outpatient clinics, area ffices. The final sample included 128 persons with stroke (acute = 49: right CVA = 28; left CVA = 19; other = 2; chronic = 70: right CVA = 39; left CVA = 35; other = 5). Detailed participant characteristics are presented in Appendix A. Participants with stroke were included in this study according to the following criteria: Inclusion criteria: (1) 20 to 89 years of age, (2) confirmed diagnosis of stroke (ischemic or intracerebral hemorrhage) based on medical records, (3) acute (7 21 days post onset) or c hronic stroke (three months to one year) (4) English speaker. Exclusion criteria: (1) subarachnoid hemorrhage, brainstem stroke, intracranial hemorrhage due to rupture aneurysm

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32 or arteriovenous malformation, (2) previous stroke on the same side of the bra in, lateral sclerosis, multiple sclerosis, dementia), (4) history of head trauma that resulted in residual neurological deficits, (5) legal blindness or severe visual impairment (6) history of significant psychiatric illness (such as bipolar affective disorder, psychosis, schizophrenia, or medication refractory depression) that affects their cognitive function, (7) unresponsive to stimulation, (8) unintelligible to others, or un able to speak, (9) global aphasia (unable to understand or express). 2.2 Data Analysis 2.2.1 Unidimensionality Unidimensionality: Historically, methods used to evaluate dimensionality include factor analysis, 32 principal componen ts analysis (PCA), 56 and item response theory fit statistics. 1 Examining item banks for unidimensionality, some modern test theory investigators propose performing a confirmatory fac tor analysis (CFA) followed up with an exploratory factor analysis (EFA) if the model shows poor fit. 73 Other researchers suggest performing a PCA of standardized residuals, after removing the primary Rasch dimension, a s a PCA will optimize the likelihood of uncovering a secondary dimension. Each approach has merits. Primarily due to a low subject to item ratio, we chose to conduct an EFA followed by a PCA of the standardized residuals. This allowed us to explore fact or structure for the entire measure, as well as examine possible second dimensions at the item level for each domain. 56

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33 2.2.2 Subject to item ratio and item parceling Though guidelines for necessary sample size and subject to item ratio to perform a factor analysis vary, 33, 60 Guadagnoli & Velicer 33 found stability of factor solutions produced with su bject to item ratio as small as 3 to 1. The subject to item ratio in our dataset was small, .52. One solution investigators have used to handle small sample size is to parcel the items into a smaller number of groups. Thus, prior to EFA, items within eac h hypothesized domain were randomly assigned to one of three parcels, and the mean of each parcel was calculated. Further, as evaluation of normality indicated high skewness and kurtosis statistics, and a non normal distribution, the data was normalized u sing a Blom transformation. 6 The transformed dataset had acceptable distribution statistics. 2.2.3 Dimensionality Analysis Exploratory factor analyses were computed in SPSS v 21 40 u sing principle axis factoring with promax rotation. Initial evaluation of number of factors to 42 and examination of the scree plot, 13 suggested retaining four or five factors. Thus, the initial proposed ten factor solution was assessed as well as the four and five factor solutions. Factor loadings greater than .35 were interpreted. 28 Root Mean Square Residual (RMSR) was calculated to evaluate model fit. RMSR, one of the few statistics available in EFA, compares the residuals from the reproduced to the observed correlations. RMSR < .05 suggests adequate model fit. 28 Additionally, when performing an EFA, beyond examining the strength of factor loadings, investigators evaluate interpretability of solutions. Interpretability evaluates if the solution is compatible with what we know from th eory and

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34 qualitative work. The ideal factor solution has high loadings on interpretable factors. Alternatively, split loadings, when items fall on two or more factors, with smaller loadings, the solution interpretation may lack clarity. Finally, a PCA of standardized residuals was computed in WINSTEPS software. 58 If a secondary dimension is detected, indicated by an eigenvalue greater than 2 (the strength of at least two items), contrasting items are evaluated for con tent. In this manner, contrasting items that load on a secondary dimension can be evaluated on a theoretical basis. It is important to note that a given domain may include subdomains. For example, the reading and writing domain in the MFC S includes rea ding and writing items that may load differently on a second dimension. In this instance, in order to assure an unbiased measure, an equivalent amount of reading and writing items would need to be included in an abbreviated form of the measure. 2.3 Results 2.3.1 Ex ploratory Factor Analysis All factor solutions, four, five and ten, contained item parcels that split loadings on factors. Specifically, the attention and executive function domains consistently split loadings on factors, with split loadings also observed within the emotional function domain (four factor solution) and within the social language and limb praxis domain (five factor solution). As the purpose of this study was to investigate dimensionality of the ten domains of the MFC S, and how they relate we report the interpretation of the ten factor solution, including the correlation of factors. Appendix B and C present the pattern matrix loadings for the four (Appendix B) and five (Appendix C) factor solution, for the interested reade r.

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35 Tab le 2 1 displays the pattern matrix for the conceptualized ten domains. Heywood cases indicate multicollinearity in the data, and examination of the factor correlation matrix revealed many high correlations ranging from .19 between limb praxis and languag e to .79 between memory and attention. Eighty seven percent of the correlations were above .4. In fact, a second order EFA, shown in Table 2 2 demonstrated evidence for a higher order general cognition factor. Factor loadings for all 10 functional cogn ition domains were above .4. The ten factor solution explained 74% of the variance prior to rotation. RMSR < .02, suggest adequate model fit. Examining the items that load on factors suggest the following interpretation of components: (1) numerical calc ulation, (2) limb praxis, (3) visuospatial ability, (4) reading and writing, (5)memory/verbal memory, (6) emotional function/inhibition and shifting, (7) social language, (8) executive function/updating, (9) language, and (10) attention. The first three f actors in Table 2 1 had strong clear loadings on the numerical calculation domain, the limb praxis domain and the visuospatial domain. The remaining factors were interpreted as follows: Reading and writing items strongly load on factor three with a small loading of one attention parcel. Some of the attention items included reading and writing attention items. Interpretation of this factor is that it represents reading and writing. Memory items strongly load on factor five with moderately strong loading of one verbal item parcel and a negative small to moderate loading of emotional function. The interpretation of this factor is that it represents memory and verbal memory. Emotional function items strongly load on factor six, with moderate loadings fro m executive function and small loadings from social language. This factor appears to contain emotional function and the inhibition and shifting pieces of executive function associated with social emotional function.

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36 All social language item parcels had mo derate to strong loadings on factor seven. Factor seven was interpreted as social language. Factor eight had moderate to strong positive loadings from two executive function item parcels and one moderate negative loading from the second language item parc el. We interpreted this factor as executive function/updating. Updating is a form Factor nine consisted of strong positive loadings from two of the language item parcels. This factor was interpreted as language. Lastly, factor ten consisted of two stron g positive loadings from two of the attention domains. We interpreted this factor as attention. 2.3.2 Principle Components Analysis on Residuals Table 2 3 summarizes PCA of standardized residuals results for the ten domains. The primary Rasch dimension for eac h domain explained a substantially higher amount of variance, ranging from 38% of the variance for the emotional function domain to 76% of the variance for the memory domain. Additional unexplained variance accounted for by secondary dimensions ranged fro m 2.7% for the memory domain to 9.7% for the limb praxis domain. Further, secondary dimensions represented conceptualized subdomains of the construct. Appendix D details contrasting items on a second dimension, for each domain, using PCA of the standardized residuals, following removal of the primary Rasch component. Secondary domain dimensions interpretations: (1) language receptive and expressive language items contrasted on a second dimension, (2) reading & writing secondary dimension ite ms contrasted on reading and writing items, (3) limb praxis secondary dimension items separated along a movement/receptive dimension, (4) visuospatial a secondary dimension contained items specific to hemispatial neglect, (5) social language items tha t fell on a second dimension included receptive and expressive language items,

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37 (6) emotional function secondary dimension items fell on an emotional lability/empathy continuum, (7) attention items loading on a second dimension fell along an action (wri ting or copying)/ passive (watching TV) continuum, (8) executive function secondary dimension items fell on a mental fatigue continuum, and (9) memory secondary dimension items fell on a n episodic or semantic memory continuum or possibly a receptive/ex pressive continuum. The only domain that did not reveal a second dimension with an eigenvalue greater than 2 was numerical calculation. 2.4 Discussion This study examined the dimensionality of a measure of functional cognition for persons with stroke. The f indings generally support the use of ten domains in the MFC S. However, these ten domains are highly correlated and many of the domains had split loadings between factors. Exploratory factor analysis suggested adequate fit for a ten factor structure of th e MFC S, with a RMSR < .02, and reasonable interpretability of factors. Four conceptualized factors had split loadings: social language, executive function, attention, and language. A consideration of prior work may aid interpretation of these split load ings. For example, there is evidence that the executive function and attention constructs may contain other lower order factors. Prior factor analysis of executive function indicates this construct encompasses three interrelated factors: updating, inhibi tion and shifting. 52, 64 Similarly, the attention domain is thought to include several subdomains, such as sustained or divided attention. 77 Additionally, verbal ability has predicted everyday memory ability. 88 In this study, one language item parcel loaded positively on the

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38 ween the social language and emotional function. Given that social ability is at least in part reliant on understanding emotions, this is not surprising. It should also be noted that during qualitative item development, some theorized cognitive stroke dom ains were combined into a single domain. For example, expressive and receptive aphasia were combined into one language domain. Further, items in some domains crossed other domains, as might be expected when developing everyday items. For example, the at tention domain contained items related to attention that included tasks or reading and writing: Thus, it is not surprising that some item parcel domains split loadings across fact ors. Further, there is extensive work examining the factor structure of cognition that indicates cognitive domains are highly correlated. Especially pertinent to this sample, these findings can be viewed within the framework of dedifferentiation in aging That is, as persons age, mental abilities become increasingly related. 4, 19 It is not surprising then that we found strong loadings on a higher order general cognition factor in thi s study, with aging, neurologically impaired persons. Though the EFA evidenced strong relatedness and split loadings, the PCA of standardized residuals supports using each of the ten domains of the MFC S as essentially unidimensional. In spite of the fac t that secondary dimensions were found, the primary measurement construct was inclusive of these smaller

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39 dimensions. Further, the primary Rasch construct explained a substantial amount of the variance over additional variance explained by possible second than that found in a comparable measure, the applied cognition scale (ACS). 17 Coster and colleagues found 10.4% residual variance in the ACS The residual variance in our domains ranged from 2.7% for the memory domain to 9.7% for the limb praxis domain. This may be partially due to the ACS containing one general domain whereas the MFC S detailed ten cognitive domains. As cognition is thought to encompass subdomains, it is logical that a measure that did not distinguish separate domains would have higher residual variance. Before concluding, we note four limitations of this study. First, our sample size was relatively small and includ ed both acute and chronic, as well as right and left hemisphere persons with stroke. Thus, sample size and heterogeneity may have affected the power of this study. Second, while item parceling improves the distributional properties of our data, the item level information is lost, hindering interpretation of the EFA. Third, our sample excluded persons more severely affected with stroke, which may limit the generalization of these findings to the larger stroke population. Lastly, the ten factor solution h ad eight loadings greater than one, indicating redundancy between the ten factors. Future dimensionality work might find other factor solutions to be a more parsimonious, better fit. 2.5 Conclusion The ideal Rasch model is perfectly unidimensional, but empiri cally, we can never expect pure unidimensionality. This may be particularly relevant when a

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40 measure evaluates every day function through self report. Instead, we rely on theory and prior knowledge to evaluate secondary dimensions through item content. Due to evidence of secondary dimensions, as the measure is further developed, it will be important to include equivalent numbers of items reflecting secondary domains.

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41 Table 2 1 Pattern matrix for 10 factor solution Factor Domain 1 2 3 4 5 6 7 8 9 10 Numerical Calculation Parcel 1 .766 Numerical Calculation Parcel 2 .413 Numerical Calculation Parcel 3 1.081 Limb Praxis Parcel 1 .520 Limb Praxis Parcel 2 .784 Limb Praxis Parcel 3 .920 Visuospatial Parcel 1 .548 Visuospatial Parcel 2 1.010 Visuospatial Parcel 3 .961 Reading & Writing Parcel 1 1.051 Reading & Writing Parcel 2 1.241 Reading & Writing Parcel 3 .699 Memory Parcel 1 .896 Memory Parcel 2 .973 Memory Parcel 3 1.169 Emotional Function Parcel 1 .771 Emotional Function Parcel 2 .781 Emotional Function Parcel 3 .463 1.219 Social Language Parcel 1 .395 .467 Social Language Parcel 2 .858 Social Language Parcel 3 .444 Executive Function Parcel 1 .392 .458 Executive Function Parcel 2 .757 Executive Function Parcel 3 .523 Language Parcel 1 .652 Language Parcel 2 .665 .447 Language Parcel 3 1.003 Attention Parcel 1 .855 Attention Parcel 2 Attention Parcel 3 .374 1.014 Note: Factor interpretation is as follows: (1) Emotional Function; Inhibition and Shifting, (2)Memory; Crystallized Intelligence, (3) Reading and writing; Sensory Processing. (4) Numerical calculation, (5) Visuospatial, (6) Limb Praxis, (7) Language; Expressive Speech, (8) Attention, (9) Social Language, (10) Executive Function; Upd ating.

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42 Table 2

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43 Table 2 3 Summary of PCA of standardized residuals CONSTRUCTS Language (13 Items) Reading & Writing (14 Items) Numerical Calculation (9 Items) Limb Praxis (10 Items) Visuo spatial (31 Items) Social Use of Language (32 Items) Emotional Function (40 Items) Attention (25 Items) Executive Function (41 Items) Memory (29 Items) Variance explained by measure 59.6% 72.5% 66.4% 57.7% 64.4% 48% 37.5% 55.9% 40.7% 75.9% Percent of unexplained variance explained by second factor 6.5% 5.7% 9.7% 3.6% 6.9% 7.7% 4.6% 8.3% 3.6% Eigenvalue of 1 st residual PCA 2.1 2.9 1.8 2.3 3.2 4.2 4.9 2.6 5.7 3.2

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44 CHAPTER 3 MEASURE OF FUNCTIONAL COGNITION IN STROKE: RASCH ANALYSIS Recent research indicates that cognitive impairment has a significant impact on post stroke recovery. 85 Additionally, though cognitive impairment can predict functional outcome in persons with stroke, 24, 25, 67, 85 and as much as 70% of persons with stroke experience cognitive impairment, existing measures of everyday functional cognition for pe rsons with stroke are limited in the breadth and depth of items, 18 or do not include tasks and domains specific to cognitive stroke impairment. 9 For example, th e Functional Independence Measure (FIM) contains ratings of ability level for only three general cognitive items: memory, orientation and problem solving. 24, 47 Many health outcomes resea rchers are increasingly turning to item response theory methods (described below) to develop and evaluate new and existing scales. Coster and colleagues 17 recently used Rasch analysis, also called the one paramete r item response theory model, to develop an applied cognition scale (ACS). Their study used a convenience sample that included persons with neurological impairment, including persons with stroke, yet items did not conceptually integrate unique symptoms as sociated with stroke. Further, though the 46 item ACS improves the measurement breadth of functional cognition, included items did not distinguish between separate cognitive constructs. Cognitive researchers have shown a general dimension of cognition t hat encompasses many subdomains. 2, 12, 62, 78 In an effort to include conceptualized cognitive subdomains for persons with stroke, our resea rch team developed a measure of functional cognition for persons with stroke (MFC S). The development process, described in detail in Donovan, 2008, 23 included a literature review, input from an expert

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45 advisory pa nel, focus groups and cognitive interviews. The final 244 item bank crossed 10 domains: Language, Reading & Writing, Numerical Calculation, Visuospatial, Limb Praxis, Social Language, Emotional Function, Attention, Executive Function and Learning & Memory We chose Rasch analysis 8 to evaluate each of the domains. Rasch measures allows for equal interval level measurement by converting scores to a logit scale. 8 That is, a score of 1 logit is ex actly one more than a score of 2 logits. To illustrate, the Rasch model presents items on an item difficulty hierarchy, and calculates a person score likely to pass m ore difficult items, and persons with less ability will be less likely to pass more difficult items. Through examination of the item hierarchy, and fit statistics, Rasch methods allow for examination of a measure at the item level rather than the test l evel. Further, Rasch modelers propose that it is better to fit the data to the model than to fit the model to the data. 54 By fitting the data to the model, misfitting items or persons can be identified, with fit statist This paper evaluates and presents the Rasch psychometrics of the MFC S. Specifically, item and person misfit, scale analysis and item hierarchy are evaluated. 3.1 Methods 3.1.1 Participants Approval for this study was obtained through the IRB 01 at the University of Florida. Each participant signed an informed consent approved by the IRB. Participants were recruited at local rehabilitation hospitals, outpatient clinics, area persons with stroke

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46 (acute = 49: right CVA = 28; left CVA = 19; other = 2; chronic = 70: right CVA = 39; left CVA = 35; other = 5). Detailed participant characteristics are presented in Appendix A. Participants with stroke were included in this study acc ording to the following criteria: Inclusion criteria: (1) 20 to 89 years of age, (2) confirmed diagnosis of stroke (ischemic or intracerebral hemorrhage) based on medical records, (3) acute (7 21 days post onset) or chronic stroke (three months to one year ) (4) E nglish speaker. Exclusion criteria: (1) subarachnoid hemorrhage, brainstem stroke, intracranial hemorrhage due to rupture aneurysm or arteriovenous malformation, (2) previous stroke on the same side of the brain, (3) preexisting neurological diseas amyotrophic lateral sclerosis, multiple sclerosis, dementia), (4) history of head trauma that resulted in residual neurological deficits, (5) legal blindness or severe visual impairment, (6) history of significant psychiatri c illness (such as bipolar affective disorder, psychosis, schizophrenia, or medication refractory depression) that affects their cognitive function, (7) unresponsive to stimulation, (8) unintelligible to others, or unable to speak, (9) global aphasia (unab le to understand or express). 3.1.2 Instrumentation The MFC S, presented in Appendix E contains 244 items that cross 10 domains: language 12 items, reading/writing 14 items, numeric calculation 9 items, limb praxis 10 items, visuospatial function 31 i tems, social use of language 32 items, emotional function 40 items, attention 25 items, executive function 41 items, memory 29 items. Construct development is described in detail in Donovan et al 2008 9 and focus group methods in a manuscript in preparation.

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47 3.2 Administration procedures The MFC S was administered to patients along with several other screening instruments and assessments. Research assistants, trained by neuropsychologists, administered al l assessments within the hospital room (acute patients) or within the following order: 1) demographics, 2) MFC S (Appendix E ), 3) NIH Stroke Scale, 4) Center for Epidemiology Studies Depression Scale (CESD), 5) anosognosia screen, 6) Modified Rankin Scale, 7) Stroke Impact Scale (participation section), 8) global cognitive fu nctioning scale pre stroke, 9) global cognitive functioning scale current and 10) selected neuropsychol ogical assessments for a random set of 50 percent of participants. The order of the administration of the MFC S domains was counterbalanced. The MFC S was administered in a self report format (versus interview format) for 43 percent of the patients. 3.3 Dat a analysis 3.3.1 Unidimensionality Rasch models require that an instrument is unidimensional. Unidimensionality, and assumption under item response theory (IRT), assumes that a person's score on a test is the result of their ability level on the construct measu red, rather than other unmeasured constructs. Unidimensionality was evaluated, detailed in a manuscript under preparation, using exploratory factor analysis and a principal components analysis of standardized residuals for each of the ten domains. Result s generally supported unidimensionality of the domains, with each domain loading on a second order, functional cognition factor.

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48 3.3.2 Rasch Analysis Rasch analysis was conducted on each functional cognition domain. Specifically, each domain was evaluated on fi ve features: (1) Rating scale analysis, (2) Fit and reliability statistics, (3) Item difficulty hierarchy, (4) Ceiling and floor effects, and (5) Person separation. First, a rating scale analysis was performed. Linacre 57 proposes three essential criteria for optimal scale performance: (1) A minimum of ten observations should be observed in each rating scale category to provide unbiased step calibrations between categories, (2) Monotonicity: category measures were exami ned to assure they increase or decrease consistently as categories advance. (3) Outfit mean square (MnSq) for each rating category are below 2.0. Under the Rasch model, a reasonable amount of randomness, or noise, is expected. The MnSq statistic of 1 indicates there is uniform variance of the data. Values greater than 2 suggest there is more unexplained variance than explained variance. Fit statistics were examined for each rating scale category, as well as persons and items. Second, person fit, item fit and point measure reliability statistics were estimated. Rasch analysis calculates two fit statistics. 7 The infit statistic is sensitive to unexpected y level. The outfit statistc is sensitive to departure from model expectations when item difficulty is far from a Wright and colleagues 1 suggest acceptable fit guidelines of .6 < MnSq < 1 .4, with a corresponding standardized Z score of less than 2.0 for questionnaire type measures. Less than .6 may produce misleadingly good reliability and separation estimates, but are not degrading to the measure. High fit statistics indicate that there is more

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49 observed variance than expected by the model. Thus, items and persons that had high fit statistics were flagged and evaluated for theoretical misfit. While the Rasch model does not include discrimination in item and persons calibrations, Winstep s 55 does provide item discrimination statistics. Low (<.2) item discrimination indices were flagged. 45 Misfitting persons were further evaluated for data entry errors or misunderstanding of items. Third, item hierarchy was evaluated for logical order of item difficulties, and ceiling and floor effects. For a given domain, items that conceptually are more difficult should fall on the higher part of the scale. For example, for the lang uage domain, carrying on a conversation in a distracting environment should be more difficult than responding to yes or no questions. Ceiling and floor effects are also reflected on the map. For example, in Figure 3 1, the # symbol to the left of the lin e represents persons. Persons reaching maximum or minimum scores fall at the top or bottom of the map, respectively. Finally, the precision of this measure, with this particular sample, was evaluated using person separation and strata statistics. The per son separation index indicates how much persons can be reliably separated into groups. Reliability above .6 allows for separation of persons into at least two statistically different groups. 1, 27 The strata index is computed from the person separation index and indicates the number of statistically distinct ability levels the sample can be divided. 3.4 Results MFC S Psychometrics are presented in Table 3 1.

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50 3.4.1 Language teria for rating scales were met. All items met infit and outfit criteria. Three percent (4) of persons indicated high infit and outfit statistics. Two percent (2) of persons had high infit statistics. Further evaluation of the misfitting persons indic ated that one person may have misunderstood simple language items lunch," or "tire conversation without mistakes. 3.4.2 Item Person Map Figure 3 1 presents the language item person map. The #s to the left of the vertical line represent two persons. Persons with higher ability are at the top, and those with lower ability at the bottom. Items are shown on the right. Items with higher difficulty are at the top, and those with lower difficulty at the bottom. Evaluating the iling effect was evident with 11% (14) of persons demonstrating maximum extreme scores. On the average people performed better than the item difficulties with the person mean at 1.68 logits +/ 1.4, and the item mean at 0 +/ .55. The person separation i ndex was 1.56 indicating persons were separated into 2.4 statistically distinct strata.

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51 3.4.3 Reading & Writing Rasch model. Eight percent (10) of persons indicated high fit stat istics: 5% (6) with high infit and outfit statistics, 2% (3) with high infit only, 1% (1) with high outfit only. 3.4.4 Item Person Map Figure 3 2 presents the reading and writing item person map. Evaluating the item difficulty logic, conceptually more difficu easiest item. A ceiling effect was evident with 17% (21) of persons demonstrating maximum extreme scores. One person had the minimum extreme score. On the average, people performed better than the item difficulties with the person mean at 1.01 logits +/ 1.78, and the item mean at 0 +/ .56. The person separation index was 1.84 indicating persons were separated into 2.79 statistically distinct strata. 3.4.5 Numerical Calculation Rasch model. Five percent (7) of persons indicated high fit statistics: 4% (5) with high infit and outfit statistics, t wo with high infit only. 3.4.6 Item Person Map Figure 3 3 presents the numerical calculation item person map. Evaluating the restaurant bill for separate payments among diner was evident with 18% (23) of persons demonstrating maximum extreme scores. On the average, people performed better than th e item difficulties with the person mean at

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52 1.16 logits +/ 1.49, and the item mean at 0 +/ .69. The person separation index was 1.34 indicating persons were separated into 2.12 statistically distinct strata. 3.4.7 Limb Praxis a for rating scales were not met. Though all rating scale categories had counts of 10 or greater and observed measures increased with higher ratings, the outfit MnSq = 2.24 for rating category one, exceeding the criteria of 2.0. Thus, the rating scale wa s collapsed to three categories. After collapsing categories, all three essential ratings scale criteria were met. outfit statistics. Seven percent (9) persons indicated high fit statistics: 5% (6) with high infit and outfit statistics, and 2% (3) with high infit only. 3.4.8 Item Person Map Figure 3 4 presents the limb praxis item person map. Evaluating the item difficul easiest item. A ceiling effect was present with 19% (24) of persons demonstrating maximum extreme scores. People performed much better than item difficulties with the person mean at 3.33 +/ 1.76 logits higher than item difficulty at 0 +/ 1.02. The person separation index was 1.01 indicating persons were separated into 1.68 statist ically distinct strata. 3.4.9 Visuospatial

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53 index. Seven percent (9) persons indicate d high fit statistics: 5% (7) with high infit and outfit statistics, 2% (2) with high outfit only. 3.4.10 Item Person Map Figure 3 5 presents the visuospatial item person map. Evaluating the item ability was fairly well matched to item difficulty with the p erson mean was .81 logits higher than item difficulty (anchored at 0). The person separation index was 2.0 indicating persons were separated into 3.0 statistically distinct strata. 3.4.11 Social Use of Language were not met. Though all rating scale categories had counts of 10 or greater and all MnSq were < 2, observed measures did not increase monotonically as rating scale categories increased. Specifically, the observed average measure was lower (.30) in categ ory two than in category 1 (.42). Examination of the rating scale indicated that the probability of choosing category 2 and 3 did not reach high levels for a given ability level, so these categories were collapsed. All three essential criteria were met a fter collapsing scales.

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54 (12) with high infit and outfit statistics, 1% (1) with high infit only and 1% (1) with high outfit only. 3.4.12 Item Person Map Figure 3 6 presents the social use of language item person map. Evaluating the had extreme scores. Person ability and item difficulty were well matched with the person mean at .24 +/ .59 logits, the item mean at 0 +/ 1.25. The person separation index was 1.37 indicating person s were separated into 2.16 statistically distinct strata. 3.4.13 Emotional Function outfit statistics. Twenty two percent (28) of persons indicated high fit statistics: 16% (20) with high infit and outfit statistics, 2%(3) with high outfit only and 4% (5) with high infit only. 3.4.14 Item Person Map Figure 3 7 presents the emotional function i tem person map. Conceptually more easiest item. No persons had extreme scores. Person ability was fairly well matched with item difficulty with the person mean at .81 logits +/ .6, the item mean at 0 +/ .42.

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55 The person separation index was 2.31 indicating persons were separated into 3.4 statistically distinct strata. 3.4.15 Attention Li d high outfit statistics. Further, these items had negative discrimination indices. Nine percent (11) of persons indicated high fit statistics: 6% (8) with high infit and outfit statistics and 2% (3) with high infit only. 3.4.16 Item Person Map Figure 3 8 pre sents the attention item person map. Conceptually more difficult easiest item One percent (1) of persons had extreme high scores. Person ability was fairly well matched with item difficulty with the person mean at .78 logits +/ .86, the item mean anchored at 0 +/ .46. The person separation index was 2.26 indicating persons w ere separated into 3.35 statistically distinct strata. 3.4.17 Executive Function four percent (5) had ability to do

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56 statistics: 11% (14) with high infit and outfit, 2% (2) with high infit only. 3.4.18 Item Person Map Figure 3 9 presents the executive function item person m ap. Evaluating the item was the easiest item. No persons had extreme scores. The person mean was .78 logits +/ .7, with the item mean at 0 +/ .38. The person separation index was 2.74 indicating persons were separated into 3.99 statistically distinct strata. 3.4.19 Memory et. Ten percent (3) of items high outfit statistics. Item discrimination indices revealed adequate discrimination in these items. Eleven percent (14) of persons indicated high fit statistics: 7% (9) with high infit and 1% (2) with high outfit only. 3.4.20 Item Person Map Figure 3 10 pre sents the memory item person map. Evaluating the item difficulty correctly when persons demonstrating maximum extreme scores. On average, people performed better than the item difficulties with the person mean at 1.76 logits +/ 1.51, and the item

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57 mean at 0 +/ .72. The person separation index was 2.29 indicating persons were separated into 3.39 statistically distinct strata. 3.4.21 Person misfit The demographics comparing misfitting persons to the overall group are presented in Table 3 2. Misfitting persons, on ave rage,: (1) were .5 years older, (2) scored .83 higher on the NIH stroke scale, (3) tended to be classified as moderate to severe on the Modified Rankin Scale (misfit: 74%, entire sample: 68%), (4) tended to be acute (misfit: 45.8%, entire sample: 38.3%), ( 5) tended to have high school education or less (misfit: 69.5%, entire sample: 58.6%), (6) tended to need assist to complete the measure (misfit: 66%, entire sample: 57%), and (7) tended to be of non white race (misfit: 42.4%, entire sample: 31.3%), 3.5 Disc ussion This study presents the psychometrics and item hierarchy of the 10 domains that comprise the MFC S. Results from this analysis generally support the use of the MFC S domains, except limb praxis, to evaluate functional cognition in stroke rehabili tation and research settings. Nine of the ten domains were able to separate persons into at least two statistically significant strata. Four domains emotional function (3.4), attention (3.4), executive function (4.03) and memory (3.39) separated p ersons into three or more statistically significant strata. However, the limb praxis domain did not separate people into at least two distinct groups and showed a strong ceiling effect with 19% (24) people reaching the maximum score. The language 11% ( 14), reading and writing 16% (21) and numerical calculation 18% (23) domains also exhibited a ceiling effect. This indicates that these domains may have been too easy for this sample. One solution in future work might be to add more difficult items. W hile sample ability may

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58 have affected these results, Coster and colleagues 17 found comparable Rasch person separation and reliability statistics in their more general applied cognition scale. Specifically, person separation for this scale was 1.8 and person reliability was .77 in sample of 477 persons with neurologic, orthopedic and complex medical diagnoses. Twenty five percent of their sample had extreme maximum scores. The present study, excluding the limb prax is domain, had person separation statistics ranging from 1.34 to 2.29; and person reliability from .64 to .88. 3.5.1 Item Misfit Examining the misfitting items, possible rationale for misfit includes reverse scored items, item sensitivity to a secondary dimens ion and item sensitivity to individual differences. Reverse coding items are items that were rescored to reflect higher scores representing greater ability. For example, in the MFC reverse scored so that a higher rating selection indicated more attention. Reverse coding items have been used by researchers to prevent response bias 37 but more recent investigations suggest that reverse scored items ma y have lower loadings on the primary measurement dimension and even group together loading on a second, unintended dimension. 15 Twenty six percent of all MFC S items were reverse code items and 62% of these items misfit the Rasch model. Table 3 3 presents these misfitting items. It is possible some persons misunderstood these items. That said, in the conceptual development of t he MFC S, some reverse scored items were removed or reworded if possible. The items that remained were thought to include critical logical pieces of the concept, and could not be reworded without losing the nature of the questions. Future work should kee p this in mind when evaluating these items in replication samples.

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59 Beyond, reverse coding; some misfitting items may have picked up on secondary dimensions. Three domains revealed misfitting items that might be inclusive of a that included a motor, gesture component. Second, the misfitting items in the emotional misfitting memory item 3.5.2 Person Misfit Person misfit ranged from 2% (language) to 28% (emotional function). Coster and colleagues found 8% of their sample misfit the model. 17 The demographics comparing misfitting persons to the overall group are presented in Table 3 3. A higher percentage of misfitting persons were less educated, had more severe stroke symptoms and were from non Caucasian racial groups. It is possible these factors influenced understanding or interpretation of the items. Two limitations should be considered in future research: (1) person ability and (2) self report challenges in persons with cognitive impairment. Despite the fact that this sample was of ad equate size, 59, 86 ceiling effects and mismatch for difficulty of test were evident in some domains. Though including persons with more severe impairment in future study might match the perso n ability to item difficulty better; this leads to the challenge of acquiring accurate self reports from persons with communicative impairment. Two possible solutions are to use proxy reports by clinicians or family members, or create performance based mea sures. However, investigators have found varying levels of agreement with self report. For example, McPhail and colleagues 63 found lower levels of agreement between self and proxy report in persons more cogniti vely impaired.

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60 3.5.3 Conclusion These results support the use of the MFC S in research and rehabilitation settings Though future work will further inform these results, this measure is a basis measuring functional cognition in persons with stroke. Future wo rk should focus on evaluating: (1) how the MFC S relates to other measures of cognition (2) new items that might extend the difficulty of ceiling domains (3) re conceptualizing and developing new items for the limb praxis domain and (4) evaluate the item statistics of reverse coded items.

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61 Table 3 1. Summary of Rasch psychometrics for MFC S CONSTRUCTS Language (13 Items) Reading & Writing (14 Items) Numerical Calculation (9 Items) Limb Praxis (10 Items)* Visuospatial (31 Items) Social Use of Lan guage (32 Items)* Emotional Function (40 Iems) Attention (25 Items) Executive Function (40 Items) Memory (29 Items) # Items Misfitting 0 0 0 2 3 0 4 0 3 2 # Persons Misfitting 3 10 7 12 12 13 17 15 20 14 Rating Scale Categories with 10 counts or greater 4 4 4 3 4 3 4 4 4 4 Rating Scale Categories I ncrease (Y/N) Y Y Y Y Y Y Y Y Y Y MnSQ Outfit less than 2 (Y/N) Y Y Y Y Y Y Y Y Y Y Person Separation (Extreme and Not Extreme) 1.56 1.84 1.34 1.34 1.92 1.53 2.31 2.09 2.77 2.29 Person Strata 2.4 2.79 2.12 2.12 2.89 2.37 3.4 3.12 4.03 3.39 Person Separation Reliability .71 .77 .64 .64 .79 .70 .84 .81 .88 .84 Alpha .91 .97 .96 .86 .94 .75 .89 .91 .95 .95

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62 Table 3 1. Continued CONSTRUCTS Language (13 Items) Reading & Writing (14 Items) Numerical Calculation (9 Items) Limb Praxis (10 Items)* Visuospatial (31 Items) Social Use of Language (32 Items)* Emotional Function (40 Items) Attention (25 Items) Executive Function (41 Items) Memory (29 Items) Person to measure correlation .84 .79 .77 .79 .58 .91 .86 .82 .85 .87 Person Mean (logits) SD 1.68 1.4 1.01 1.78 1.16 1.49 2.83 1.83 .84 .87 .31 .65 .81 .6 .91 1.08 .8 .73 1.76 1.51 Ceiling 14 21 23 0 3 0 0 4 0 8 Floor 0 1 0 2 0 0 0 0 0 0 Measured Missing 111 3 104 2 103 2 123 3 124 1 127 1 127 1 121 3 124 4 117 3 Collapsed to three categories because four

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63 Table 3 2. Misfitting person demographics Misfitting Person group Entire Sample Gender Male: 26 (44.1%) Female: 33 (55.9%) Male: 58 (45.3%) Female: 70 (54.7%) Age 66.34 (12.45) 65.84 (13) NIH Stroke Scale 5.23 (4.17) 4.4 (3.84) Acute or Chronic Acute: 27 (45.8%) Chronic: 32 (54.2%) Acute: 49 (38.3%) Chronic: 79 (61.7%) Modified Rankin Scale (moderate/severe) Mild: 15 (25.4%) Moderate/Severe: 44 (74.4%) Mild: 41 (32%) Moderate/Severe: 87 (68%) Stroke Location Right: 30 (50.8%) Left: 24 (40.7%) Right and Cerebellar: 1 (1.7%) Right and Subcortical: 1 (1.7%) Uncertain: 2 (3.4%) Bilateral: 1 (1.7%) Right: 69 (53.9%) Left: 52 (40.6%) Right and Cerebellar: 1 (.8%) Right and Subcortical: 1 (.8%) Uncertain: 2 (2.3%) Bilateral: 3 (2.3%) Education < High School: 16 (27.1) High School/GED 25 (42.4) Some Colle ge or more: 18 (30.5) < High School: 27 (21.1) High School/GED 48 (37.5) Some College or more: 53 (41.4) Global Assessment of Cognitive Function 1.33 (1.6) 1.41 (1.46) Assist with MFC S Assist: 39 (66%) Assist: 73 (57%) Race Black or African American: 23 (39%) White: 33 (55.9%) Asian: 2 (3.4%) Unknown: 1 (1.7%) Black or African American: 38 (29.7%) White: 87 (68%) Asian: 2 (1.6%) Unknown: 1 (.8%)

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64 Table 3 3. Reverse coding items Domain Item (s) Limb Praxis Is clumsy when using tools. Visuospatial Paralyzed limb hangs over wheelchair Bumps into doorway on left side. Gets lost in new setting. Social Language Goes on and on without giving another persons a chance to talk. Emotional Function Does not know why things are difficult. Attempts to do harmful things. Attempts tasks that require thinking skills beyond ability. Does not know why things are difficult since having a stroke. Attention Stops in the middle of a task when distracted. Pays attention to the wrong conversation. E xecutive Function Tries to do an activity before having the ability to do it. Takes things literally.

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65 Figure 3 1. Language person item map

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66 Figure 3 2. Reading and writing person item map

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67 Figure 3 3. Numerical calculation person item map

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68 Figure 3 4. Limb praxis person item map

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69 Figure 3 5. Visuospatial person item map

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70 Figure 3 6. Social language person item map

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71 Figure 3 7. Emotional function person item map

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72 Figure 3 8. Attention person item map

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73 Figure 3 9. Executive function person item map

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74 Figure 3 10. Memory person item map

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75 CHAPTER 4 A VALIDITY STUDY OF A MEASURE OF FUNCTIONAL COGNITION FOR PERSONS WITH STROKE Our research team recently developed the MFC S to encompass everyday tasks that rely heavily on cognition. 23 Cognition is thought to include multiple secondary dimensions. 10 12 Following qualitative work inc luding a literature review and expert panel recommendation, the MFC S included items specific to the cognitive impairment observed in persons with stroke, covering ten cognitive domains: (1) Language (2) Reading and writing (3) Numerical calculation (4) Li mb praxis (5) Visuospatial ability (6) Social language (7) Emotional function (8) Attention (9) Executive function and (10) Memory. A critical component to instrument development is evaluation of validity. That is, does the used measure provide a meaning ful outcome score given the intended goal? 16 Determining the validity of a newly developed applied cognitive measure is important, especially since this instrument intends to capture the implications of cognitiv e deficits on everyday life. Two types of evidence used to evaluate validity include: (1) comparing an instrument to other instruments thought to measure a similar construct, and (2) evaluating how an instrument predicts group membership. 16 Cognitive researchers have used more fundamental measures of cognition, as well as existing every day measures thought to measure a similar construct to examine concurrent validity. 2 Additionally, the ten domains of the MFC S were developed based on cognitive impairments observed in persons with stroke. For example, persons with a left sided cerebrovascular accident (CVA) are more likely to have impairments with expressive or receptive speech. Alternatively, persons with a right hemisphere CVA are more likely to experience visuospatial impairments. If the MFC S measures the functional cognition of

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76 stroke, we should be able to predict whether a person has a left or right hemi sphere CVA. This study examines the validity of the MFC S, answering two questions. First, what is the relationship between person scores measures on the MFC S and traditional neuropsychological measures of cognition from similar domains? Second, can the MFC S predict group membership? That is, does the profile of person scores, and for which domains, predict whether a person has had a right or left hemisphere stroke? 4.1 Methods 4.1.1 Participants Approval for this study was obtained through the IRB 01 at the Un iversity of Florida. Each participant signed an informed consent approved by the IRB. Participants were recruited at local rehabilitation hospitals, outpatient clinics, area ied random sample, based on acute/chronic and mild (Modified Rankin score 0 2) or moderate (Modified Rankin Score (3 5), from the larger sample (n=128) who took the MFC S. This sample included 62 persons with stroke (acute = 22: right CVA = 17; left CVA = 3; other = 2; chronic = 40: right CVA = 19; left CVA = 16; other = 5). Detailed participant characteristics are presented in Table 4 1. Participants with stroke were included in this study according to the following criteria: Inclusion criteria: (1) 20 to 89 years of age, (2) confirmed diagnosis of stroke (ischemic or intracerebral hemorrhage) based on medical records, (3) acute (7 21 days post onset) or chronic stroke (three months to one year) (4) english speaker. Exclusion criteria: (1) subarachnoid hemorrhage, brainstem stroke, intracranial hemorrhage due to rupture aneurysm or arteriovenous malformation, (2) previous stroke on the same side of the brain, (3) preexisting neurological disease (such

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77 s, multiple sclerosis, dementia), (4) history of head trauma that resulted in residual neurological deficits, (5) legal blindness or severe visual impairment, (6) history of significant psychiatric illness (such as bipolar affective disorder, psychosis, sc hizophrenia, or medication refractory depression) that affects their cognitive function, (7) unresponsive to stimulation, (8) unintelligible to others, or unable to speak, (9) global aphasia (unable to understand or express). 4.1.2 Instrumentation 4.1.2.1 The MFC S The MFC S is a questionnaire type measure that includes 244 items over 10 domains: language 12 items, reading/writing 14 items, numeric calculation 9 items, limb praxis 10 items, visuospatial function 31 items, social use of language 32 items, emo tional function 40 items, attention 25 items, executive function 41 items, memory 29 items. Respondents rated their ability of performing a task in the past week on a 4 point likert scale. Example items include: (1) Responds to simple yes or no questions either by nodding, gesturing, or speaking, and (2) Has trouble making plans for the future. Traditional Neuropsychol ogical l Measures: Table 4 2 presents MFC S domains and corresponding neuropsychological measures, described further below. 4.1.2.2 Repeat able Battery for the Assessment of Neuropsychological Status (RBANS ) 72 The RBANS has been used to screen general cognitive function in a variety of diagnoses 31, 38, 50, 51, 65, 69, 72 including pers ons with stroke The RBANS contains 12 subtests that constitute 5 index scores: (1) The immediate memory index comprises the subtests of list learning and story memory; (2) Figure copy and line orientation yield the

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78 visuospatial/constructional index; (3) Picture naming and semantic fluency yield the language index; (4) the attention index contains the digit span and coding subtests; (5) the delayed memory index includes list recall, list recognition, story recall, and figure recall subtests. We used: (1) t he language index score to examine relationship with the MFC S language domain; (2) index score of visuospatial construction to examine relationship with the MFC S visuospatial domain; (3) the index score of immediate memory and the index score of delayed memory to examine relationship with the MFC S learning and memory domain; and (4) the index score of attention to examine relationship with the MFC S attention domain. 4.1.2.3 Digit Symbol Coding The Digit Symbol Coding, a subtest of the Wechsler Adult Intelligen ce Scale third edition (WAIS III) 87 was used to assess processing speed. A list of matched numbers and symbols is presented to the participant who is then asked to copy the symbols under the boxes of the numbers as fast as they can within 120 seconds. The number of correct responses is recorded. The WAIS III coding scale was seleted to compare to MFC S scores on the attention domain. 4.1.2.4 Behavior Rating Inventory of Executive Functions Adult (BRIEF) The Behavior Rating Inv entory of Executive Function Adult Version (BRIEF A) contains eight subscales. 74 The BRIEF is a questionnaire consisting of 75 items assessing executive behaviors. Three point rating scale of the BRIEF ranges from 1 to The Emotional Control subscale scores were compared to the MFC S emotional function scores. The inhibit, shift, metacognition, and self monitor scores were comp ared to the MFC S executive function scores.

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79 4.1.2.5 Functional Assessment of Communication Skills for Adults (ASHA FACS) 30 The ASHA FACS contains a social communication subscale of 21 items. On a seven point rating scal communication subscale was compared to the MFC S social language score. 4.1.2.6 Center for Epidemiologic Studies Depression Scale (CES D) The CES Dis a 20 item self depression domains: depressed mood, feeling of worthlessness, feeling of helplessness, psychomotor retardation, loss of appetite and sleep disturbance The questionnaire is rated on the frequency of experiencing depression related symptoms in the past week. The four point scale ranges from 0 rarely or none of the time to 3 most or all of the time. CES D scores range from 0 60 with higher scores i ndicative of higher depression symptoms. CES D scores were compared to MFC S emotional function scores. 4.1.2.7 Wechsler Individual Achievement Tests (WIAT II) 79 The WIAT II is a standardized test for measuring achiev ement. The full length assessment contains 9 subscales to assess academic achievement. We used the Word Reading, Spelling and Numerical Calculation subtests to examine the relationship with: (1) the MFC S reading & writing domain (WIAT II word reading and spelling); and (2) the MFC S numerical calculation domain (WIAT II numerical calculation). 4.1.2.8 Trails A & B The Trail Making Test (TMT) is a timed test and includes parts A and B, which are both visual scanning tasks. 80 The TMT integrates recognition of numbers and

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80 letters and perception of spatial distribution. The Trails A requires connecting dots in sequential order of numbers whereas the Trails B requires connecting dots alternating sequential letters and numbers We used the Trails A index score to examine the relationship with the MFC S attention domain. The Trails B index score, and the Trails B/A raw score to examine the relationship with the executive function domain. 3 Some investigators have used the difference score between Trails A and B or the ratio of the Trails B to A to differentiate the processing speed component of Trails A from the switching component of Trails B. 49 4.1.2.9 Delis Kaplan Executive Functions Scale (D KEFS) Sorting Test 20 The D KEFS Sorting Test has two parts: a sort recognition condition and a free sort condition. In the free sorting condition the participant so rts cards into groups according to stimulus words or patterns on the cards. In the sort recognition condition the examinee attempts to describe the grouping rule the examiner uses to sort the cards. The D KEFS Sorting allows for evaluation of several com ponents of executive function such as problem solving, initiation and inhibition. The scores of the sorting test were compared to the MFC S executive function score. 4.1.2.10 Mini Florida Apraxia Battery (Mini FAB) The Florida Apraxia Battery (FAB) was chosen to assess praxis ability and has been used in studies with persons with stroke 29, 35, 68, 70, 75 Subtest 5, gesture to instruction to gesture or pretend to use a tool as if they were actually holding the tool in the hand. Persons were scored pass/fail if they could perform the gesture on 30 praxis items. FAB scores were com pared to MFC S limb praxis domain scores.

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81 4.1.3 Administration Procedure Research assistants, trained by a neuropsychologist, administered all the assessments. Assessment sessions occurred within the hospital room (acute patients), S was administered in a self report fo rmat (versus interview format) 43 percent of the time for patients. As with the MFC S domains, the ordering of the neuropsychological/ functional assessment battery was counterbalanced. 4.1.4 Data Analysis Correlation, profile analysis and logistic regression were used to evaluate the validity of the MFC S. Pearson correlations were computed in SPSS vs 21 40 between the neuropsychological measures and the corresponding domains of the MFC S to examine the relations hip between the traditional neuropsychological measures and the MFC S domains. In order to control for family wise error rate, for each domain that had more than one comparison, we report the p value from the statistical output, then use the Bonferroni co rrection 26 = .05 level. So, if there are three comparisons for a domain, we would need the reported p value to be .05/3 = .017 to reach statistical significan ce, controlling for multiple comparisons. We predicted to find significant correlations between comparable constructs. Next, a profile analysis was done comparing right hemisphere CVA and left hemisphere CVA groups. As persons with stroke often presen t with cognitive impairment based on the side of their CVA, we predicted that persons with left and right hemisphere stroke would present with a different pattern of scores. Lastly, we

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82 performed a logistic regression; following the profile analysis to ass ess which domains significantly predicted group membership (i.e. left or right hemisphere CVA). 4.2 Results 4.2.1 Correlation with concurrent measures Table 4 3 presents the correlation results for the MFC S domains with comparison measures. Seven of the ten do mains had statistically significant correlations with at least some of the comparison measures. Significant correlations ranged from .26 between the ASHA FACS and the social language domain to .62 between the BRIEF shift subtest and the executive function domain. P values available from the statistical output are reported. Two significant p values could be considered non significant, at the p < .05 level, with Bonferroni correction: (1) The RBANS immediate memory in the memory domain (Bonferroni correcti on p value = .025) and (2) the D KEFS Sort Recognition in the executive function domain (Bonferroni correction p value = .006). 4.2.2 Profile Analysis Figure 4 1 illustrates the profile of MFC S domain scores comparing persons with a left CVA to right CVA. From visual inspection, persons with a left CVA tended to perform worse on all domains except the language and visuospatial domains. Data screening was done and three persons had missing data so were removed from further analysis. In order to meet the commens urate scales assumption, the scores from each significant at the .001 level, F(55, 38018) = 1.342, p = .05, but our sample sizes were unequal: right CVA: n=62, left CVA: n=52. significant for unequal variances, assumptions were satisfied to proceed with the

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83 analysis. The test for equal levels between groups was not significant. The test for s significant F(9, 104) = 2.44, p = .015. 4.2.3 Logistic regression The model including all ten domains was significant X 2 (10) = 24.79, p = .006, correctly classifying persons with right CVA 74.2%, and persons with left CVA 57.7%. The regression coefficients for the language domain Wald (1) = .846, p = .004 and visuospatial domain Wald (1) = 7.66, p = .005 were statistically significant. Interpreting these regressions coefficients, displayed in Table 4 4, the odds that a person had a right CVA, rather than a left CVA, are 70% less likely for one logit increase in language, and 65% less likely with a one logit increase in visuospatial. 4.3 Discussion Validity of the MFC S was supported by findings of moderate to strong correlations 3 6 for seven of the domains: Language, reading and writing, visuospatial, social language, emotional function, executive function and memory. Further, the profile analysis predicted group membership for right or left CVA with significant predictors of language and visuospatial scores. Alternatively, two possible validity challenges are noted. First there was a lack of a relationship to comparison measures for the numerical calculation, limb praxis, and attention domains, and for the WIAT II spelling sc ore to the reading and writing domain. Second, though the profile of scores did predict the side of CVA, persons with left CVA score higher on the language domain. We might expect persons with left CVA to perform worse on the language domain based on neu roanatomical studies of stroke impairment. 9 Examining the above mentioned challenges more closely, sample selection and previous findings may help to explain these findings. This study, because o f the nature

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84 of self report, necessitated that persons with severe communication impairment were not included. This may have biased the left hemisphere group to be less inclusive of the language impairment associated with left sided CVA, thus influencing o ur results. Also, when developing items for the MFC S, there was not an intention to separate right from left CVA, but to include items that were more descriptive of the cognitive impairment observed in persons with stroke, inclusive of both right and lef t CVA symptoms. The visuospatial domain included several items that relate to left side neglect. For example: CVA. This may have impacted the predictiveness of the visuospatial scores for right vs left CVA. Further, it is notable that 9/9 of the comparison measures that did not show a relationship with the MFC S domain were comprised of performance based, measures of cognition. For example, the Trails A and Trail s B measure the speed and ability to switch, respectively, between numbers and/or letters. On the other hand, the comparison measures that significantly and strongly associated with the MFC S domain were similar self report measures of everyday ability: ( 1) the BRIEF and (2) the ASHA FAC and (3) the CESD. Some cognitive researchers propose that though there is a relationship between performance based measures of cognition and everyday ability, this relationship may be moderated by other variables such as education. 22 Limitations of this study include challenges of using a self report measure in persons with cognitive impairment, sample size limitations, and the use of univariate analyses. The nature of a self repo rt measure requires that persons are able to communicate, yet persons with stroke may experience communication challenges. One

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85 solution is to use proxy or interview formats. Yet, differences have been found between self and proxy, caregiver or health pro vider, report. Future work should consider how the MFC S self report scores relate to proxy reports, and include persons more severely affected by stroke. Further, the generalizability is limited to this sample, which included persons mildly to moderatel y affected by stroke. The NIH stroke scale score for persons of moderate to severe impairment is 15. Our sample averaged 4.54 (4.07) for the acute group and 4.31 (3.72) for the chronic group. For domains that did not related to comparison future work mi ght include performance based or questionnaire comparison measures to further evaluate validity in these domains. Lastly, sample size limitations may have affected the power of detecting relationships between comparison studies, a type II error. In contra st, while we attempted to decrease type II errors using Bonferroni corrections, this was still a possibility. 4.4 Conclusion This study presents beginning evidence that the MFC S can be used as a meaningful measure of everyday cognition for persons with stroke Interesting next questions might be to evaluate how the MFC S compares with proxy report, to other everyday performance measures of cognition and in a clinical setting. Lastly, future work with larger sample sizes will allow for further investigation of the impact of variables such as age, education and race moderate the effect between more fundamental cognitive performance on measures, such as the Trails A and B, and functional cognitive ability.

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86 Table 4 1. Participant characteristics Demographic Information of Patient (n=128) Acute (n=49) Chronic (n=79) Gender Female 27 55.10% 43 54.40% Male 22 44.90% 36 45.6 Age Mean (SD) 64.84 (12.534) 66.47 (13.335) Highest Grade Completed
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87 Table 4 1. Continued Demographic Information of Patient (n=128) Acute (n=49) Chronic (n=79) 0= no stroke 1 4= minor stroke 5 15= moderate stroke 15 20= moderate/severe stroke 21 42= severe stroke Mean (SD) 4.54 (4.07) 4.31 (3.716) SIS Participation subscale total score (n=49 chronic) Mean (SD) N/A 26.63 (7.931) Days post stroke onset Mean (SD) 14.29 (3.99) 151.92 (78.848) Stroke Type (n=127) (n=78) Ischemic 45 91.80% 60 75.90% Hemorrhagic 4 8.20% 12 15.20% Uncertain 0 6.3% 6 7.60% Stroke Location Right Hemisphere 28 57.10% 39 49.40% Left Hemisphere 19 38.80% 35 44.30% Bilateral 0 0.00% 3 3.80% Right Hemisphere & Cerebellar 1 2.00% 0 0.00% Right Hemisphere & Subcortical 1 2.00% 0 0.00% Uncertain 0 0.00% 2 2.50% Have prior stroke Demographic Information of Patient (n=128) Acute (n=49) Chronic (n=79) No 35 71.40% 58 73.40% Yes 14 28.60% 21 26.60% Prior Stroke Location (n=14) (n=5) (n=15) Same Hemisphere 3 60.00% 9 60.00% Different Hemisphere 2 40.00% 5 33.30% Bilateral 0 0.00% 1 6.70% Hand used for writing prior to stroke Right 47 95.90% 73 92.40% Left 2 4.10% 6 7.60%

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88 Table 4 1. Continued Demographic Information of Patient (n=128) Acute (n=49) Chronic (n=79) Have a history of sustained, unresolved, alcoholism or drug use No 48 98.00% 75 94.90% Yes 1 2.00% 4 5.10% Have hearing problems (n=80) (n=47) No 44 89.80% 66 83.50% Yes 4 8.20% 13 16.50% Have vision problems No 43 87.80% 58 73.40% Yes 6 12.20% 21 26.60% Use memory aids since the stroke (for example a memory book) No 45 91.80% 53 67.10% Yes 4 8.20% 26 32.90% Have weakness or paralysis since the stroke No 7 14.30% 16 20.30% Yes 42 85.70% 63 79.70% Aware of having a stroke (n=123) (n=47) (n=76) No 0 0.00% 1 1.30% Yes 47 100.00% 75 98.70% Aware of problems due to stroke (n=123) (n=47) (n=76) No 7 14.90% 8 10.50% Yes 40 85.10% 68 89.50%

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89 Table 4 2. Neuropsychological measures and associated MFC S domain Domain Neuropsychological Measure Comparison Language RBANS Picture Naming RBANS Semantic Fluency Reading & Writing WIAT II Word Reading WIAT II Spelling Numerical Calculation WIAT II Numerical Operations Limb Praxis Mini FAB Visuospatial RBANS Figure Copy RBANS Line Orientation Social Language ASHA FACS (21 items) Emotional Function CESD (Day 1) BRIEF ( Emotional Management Items) Attention RBANS Digit Span (forward) WAIS III Coding Trails A Executive Function Trails B Trails B A D KEFS Sorting (BRIEF inhibit, shift, metacognition, and self monitor scales ) Learning and Memory Immediate : RBANS List Learning RBANS Story Memory Delayed : RBANS List Recall RBANS List Recognition RBANS Story Memory RBANS Figure Recall

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90 Table 4 3. MFC S Domain correlations with neuropsychological measures Domain Measure used for Analysis Correlation Coefficient Significance 1) Language RBANS language score n = 59 .30 p = .01 2) Reading & Writing WIAT II A standard score of word reading n = 59 WIAT II A standard score of spelling n = 62 .29 .16 p = .01 p = .11 3) Numerical calculation WIAT II A numerical operation n = 62 .12 p = .19 4) Limb praxis Mini Florida Apraxia Battery n = 61 .15 p = .18 5) Visuospatial RBANS viso spatial construction n = 59 .31 p = .008 6) Social language ASHA FACS (21 items) n = 62 .26 p =.02 7) Emotional function CESD (Day 1) n = 62 BRIEF (Emotional Management Items) n = 62 .5 .47 p < .001 p < .001 8) Attention Trails A n = 62 WAIS III coding n = 56 RBANS attention n = 62 .12 .09 .12 p = .17 p = .31 p = .18

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91 Table 4 3. Continued Domain Measure used for Analysis Correlation Coefficient Significance 9) Executive function BRIEF inhibit n = 62 BRIEF shift n = 62 BRIEF self monitor n = 62 BRIEF Metacognition n = 62 D KEFS confirmed correct sorts n = 62 D KEFS free sorting description n = 62 D KEFS sort recognition n = 59 Trails B n = 61 Trails B/A Ratio n = 61 .47 .62 .51 .52 .08 .14 .30 .17 .11 p < .001 p < .001 p < .001 p < .001 p = .28 p = .15 p = .011 p = .17 p=.11 10) Learning & Memory RBANS immediate memory n = 62 RBANS delayed memory n = 62 .24 .27 p = .03 p = .02 Significant correlations.

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92 Table 4 4. Regression coefficients for binary logistic model predicting left or right CVA Domain B S.E. Wald df Sig. Exp(B) Language 1.175 .404 8.459 1 .004 .309 Read & Write 682 .404 2.857 1 .091 1.978 Numerical Calculation .115 .333 .119 1 .730 1.122 Limb Praxis .152 .281 .293 1 .588 1.165 Visuospatial 1.020 .369 7.656 1 .006 .361 Social Language .163 .250 .423 1 .515 1.176 Emotional Function .698 .391 3.176 1 .075 2.009 Attention .354 .389 .826 1 .363 1.424 Executive Function .063 .435 .021 1 .884 .939 Memory .723 .394 3.362 1 .067 2.061

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93 Table 4 5. Model classification of right or left CVA Observed Predicted Stroke Location Percentage Correct Right Left Stroke Location Right 46 16 74.2 Left 22 30 57.7 Overall Percentage 66.7

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94 Figure 4 1. L eft vs. right comparison profile

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95 CHAPTER 5 SUMMARY AND CONCLUSION Research indicates that cognitive impairment associated with stroke affects functional outcomes. 85 While important work remains to be done to determine optimal treatme nt methods, and related issues, given this information, this project was concerned with the measurement of applied cognition. Current measures to evaluate functional, or everyday, ability specifically related to cognitive impairment are limited in breadth 18 or contain neither the secondary constructs of cognition nor impairment unique to stroke. 17 5.1 Summary To that end, this project examines the psychometric properties of a measur e of functional cognition in persons with stroke (MFC S). Beginning with a review and comparison of classical test theory (CTT) and modern test theory (MTT), this project proceeded to three studies: (1) evaluation of dimensionality of the MFC S through ex ploratory factor analysis (EFA) and principle components analysis (PCA) of the residuals, (2) evaluation of the measurement properties of the MFC S using the Rasch measurement model, and (3) evaluation of the validity of the MFC S using correlation analysi s to comparison measures and a profile analysis to predict laterality of cerebrovascular accident (CVA). Study one used factor analytic techniques to examine the dimensionality of the MFC S. The EFA demonstrated support for a ten factor solution, with s econd order factors loading on a higher general factor. The PCA of residuals allowed for item level examination. Every domain, except numerical calculation, revealed a possible second dimension. But, for every domain, the majority of the variance was ca ptured by the

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96 primary Rasch component. Further, each secondary dimension was explained by constructs the primary dimension intended to capture. For example, the reading and writing domain contained both a reading and writing secondary dimension. This st udy was important since it supports measuring the individual dimensions of MFC in the population of individuals with stroke. Study two used the Rasch measurement model to assess item level psychometrics of the MFC S. Nine of the ten domains, all but limb praxis, were able to separate persons into at least two statistically different groups. Further, evaluation of the item hierarchy for each domain indicated a gradient from less difficult to more difficult items that was conceptually sound. For example, the language domain scale. Though, several of the domains showed ceiling effect s with persons from this sample reaching the maximum extreme score: language (11% (14)), reading & writing (17% (21)), numerical calculation (18% (23)), limb praxis (19% (24)) and memory (6% (8)), our sample selection criteria excluded those persons more s everely affected by stroke. On the National Institute of Health Stroke Scale (NIHSS), the mean of our acute group was 4.54 (4.07) and the chronic group was 4.31 (3.716). The NIHSS range for moderate stroke is 5 15 and the cutoff for moderate to severe str oke is 15 20. This study demonstrated that the MFC S domains (with the exception of apraxia) separate persons into statistically distinct levels of functional/applied cognitive ability. Study three examined the validity of the MFC S using correlation with comparison measures, and a profile analysis followed up by logistic regression to

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97 predict laterality of stroke. Comparison questionnaire type measures that included everyday abilities such as the Functional Assessment of Communication Skills for Adults ( ASHA FACS), 30 the Behavior Rating Inventory of Executive Functions Adult (BRIEF) 74 and the Center for Epidemiologic Studies Depression Scale (CES D) 71 had statistically significant and stronger associations with the MFC S than did the more traditional neuropsychological measures. The profile analysis indicated that profile scores associated with right or left CVA could predict group membership, i.e. in which cerebral hemisphere a person had their stroke. The language and visuospatial domains were significant predictors in a logistic regression model entering all ten domains, though language was the opposite of what we would have exp ected. That is, a person with left CVA, for this sample, tended to have a higher language scores. We posited that as this sample, selected on criterion that excluded persons with communication impairment may have affected this result. Alternatively, th e visuopsatial domain scores did predict in the expected direction. Persons with left CVA tended to do better with visuospatial ability than persons with right CVA. This study demonstrates the concurrent validity of the MFC S. 5.2 Conclusion The importance of this series of studies was that it evaluated a measure of functional, or applied, cognition in persons with stroke that incorporates secondary cognitive constructs. The above findings suggest that the MFC S can provide a profile of applied cognitive abil ities and deficits that can be the target of treatment interventions. The above findings strengthens clinicians and investigators confidence using the MFC S, specifically to me asure differences in applied cognitive ability and to relate this ability on th is measure with meaningful outcomes such as the ability to live on

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98 support. Future work needs to focus on replicating and expanding these findings. If the misfitt ing items in this study continue to misfit or not discriminate persons, removing these items should improve the measure. Additional work should focus on reexamination of the limb praxis domain. It is possible that this sample was truncated with respect t o ability, i.e., too able, for this measure to discriminate well. It is also possible that the items did not fully capture the functional limb praxis domain. This needs to be further investigated. Future work with larger sample sizes will allow for fu rther investigation of the impact of variables such as age, education and race moderate the effect between more fundamental cognitive performance on measures, such as th e Trails A and B, and applied cognitive ability. Future work should also investigate t he sensitivity of the MFC in monitoring meaningful clinical differences in patients across normal recovery and recovery followed by rehabilitation interventions. The overarching purpose of this series of studies supports the rehabilitation research goal s of developing meaningful measurement tools to assess treatment effects. 66 While this represents the initial psychometric findings of the MFC, it provides the basis for evaluating treatment interventions through meaningful outcome measures that evaluate everyday tasks that rely heavily on cognition.

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99 APPENDIX A PARTICIPANT CHARACTERISTICS Demographic Information of Patient (n=128) Acute (n=49) Chronic (n=79) Gender Female 27 55.10% 43 54.40% Male 22 44.90% 36 45.6 Age Mean (SD) 64.84 (12.534) 66.47 (13.335) Highest Grade Completed High school, GED 22 44.90% 26 32.90%
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100 Demographic Information of Patient (n=128) Acute (n=49) Chronic (n=79) Cerebellar Right Hemisphere & Subcortical 1 2.00% 0 0.00% Uncertain 0 0.00% 2 2.50% Have prior stroke No 35 71.40% 58 73.40% Yes 14 28.60% 21 26.60% Prior Stroke Location (n=14) (n=5) (n=15) Same Hemisphere 3 60.00% 9 60.00% Different Hemisphere 2 40.00% 5 33.30% Bilateral 0 0.00% 1 6.70% Hand used for writing prior to stroke Right 47 95.90% 73 92.40% Left 2 4.10% 6 7.60% Have a history of sustained, unresolved, alcoholism or drug use No 48 98.00% 75 94.90% Yes 1 2.00% 4 5.10% Have hearing problems (n=80) (n=47) No 44 89.80% 66 83.50% Yes 4 8.20% 13 16.50% Have vision problems No 43 87.80% 58 73.40% Yes 6 12.20% 21 26.60% Use memory aids since the stroke (for example a memory book) No 45 91.80% 53 67.10% Yes 4 8.20% 26 32.90% Have weakness or paralysis since the stroke Yes 42 85.70% 63 79.70% No 7 14.30% 16 20.30% Aware of having a stroke (n=123) (n=47) (n=76) Yes 47 100.00% 75 98.70% No 0 0.00% 1 1.30% Aware of problems due to stroke (n=123) (n=47) (n=76) Yes 40 85.10% 68 89.50% No 7 14.90% 8 10.50%

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101 APPENDIX B PATTERN MATRIX RETAI NING FOUR FACTORS Factor 1 2 3 4 Language Parcel 1 .451 Language Parcel 2 .646 Language Parcel 3 .558 Reading & Writing Parcel 1 .891 Reading & Writing Parcel 2 .900 Reading & Writing Parcel 3 .703 Numerical Calculation Parcel 1 .719 Numerical Calculation Parcel 2 .505 Numerical Calculation Parcel 3 .592 Limb Praxis Parcel 1 .632 Limb Praxis Parcel 2 .589 Limb Praxis Parcel 3 .726 Visuospatial Parcel 1 .682 Visuospatial Parcel 2 .686 Visuospatial Parcel 3 .806 Social Language Parcel 1 .738 Social Language Parcel 2 .624 Social Language Parcel 3 .699 Emotional Function Parcel 1 .779 Emotional Function Parcel 2 .736 Emotional Function Parcel 3 1.033 .362 Attention Parcel 1 .375 .366 Attention Parcel 2 .641 Attention Parcel 3 Executive Function Parcel 1 .406 Executive Function Parcel 2 Executive Function Parcel 3 .447 Memory Parcel 1 .851 Memory Parcel 2 .939 Memory Parcel 3 .889

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102 APPENDIX C PATTERN MATRIX RETAI NING FIVE FACTORS Factor 1 2 3 4 5 Language Parcel 1 .432 Language Parcel 2 .677 Language Parcel 3 .548 Reading & Writing Parcel 1 .897 Reading & Writing Parcel 2 .868 Reading & Writing Parcel 3 .814 Numerical Calculation Parcel 1 .844 Numerical Calculation Parcel 2 .535 Numerical Calculation Parcel 3 .966 Limb Praxis Parcel 1 .610 Limb Praxis Parcel 2 .572 Limb Praxis Parcel 3 .366 .741 Visuospatial Parcel 1 .534 Visuospatial Parcel 2 .648 Visuospatial Parcel 3 .769 Social Language Parcel 1 .799 Social Language Parcel 2 .662 .370 Social Language Parcel 3 .750 Emotional Function Parcel 1 .852 Emotional Function Parcel 2 .798 Emotional Function Parcel 3 1.129 Attention Parcel 1 Attention Parcel 2 .522 Attention Parcel 3 .415 Executive Function Parcel 1 .431 Executive Function Parcel 2 Executive Function Parcel 3 .474 Memory Parcel 1 .903 Memory Parcel 2 1.011 Memory Parcel 3 1.049

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103 APPENDIX D SECONDARY DIMENSION AFTER REMOVING PRIMA RY RASCH DIMENSION Domain (Eigenvalue) Loading Items Language (2.1) .69 .61 .41 .57 .51 .43 4. Follows 2 step directions when asked. 5. Follows multiple step directions when asked. 7. Follows a conversation in a distracting environment by appropriately nodding, smiling, gesturing. ---------------------------------------------------------------------10. Uses more than one word to express needs. 8. Answers questions correctly abou t complex information. 11. Speaks in short sentences. Reading & Writing (2.9) .68 .58 .53 .52 .49 .56 .53 .48 26. Writes a brief letter 24. Writes a short note 23. Writes a short list 27. Writes more than one paragraph 25. Completes a business form --------------------------------------------------------------------16. Reads signs in a store or hospital 15. Reads the menu in a restaurant 19. Reads a complete article in the daily newspaper or magazine Limb Praxis (2.3) .73 .52 .71 .60 .58 38. Is clumsy when using tools 37. Waves hello or goodbye ---------------------------------------------------------------------42. Chooses the righ t kitchen tool but uses it in the wrong way 43. Chooses the right grooming tool but uses in the wrong way 41. Chooses the right utensil but uses it in the wrong way Visuospatial (3.2) .74 .71 .58 .50 .46 .46 54. Eats food on left side of plate or tray. 55. Looks at left side of clock or uses left side controls on radio or TV. 53. Writes or draws on left side of paper. 56. Dresses or grooms left side of body. 52. Reads words on left side of a menu, newspaper, or book. --------------------------------------------------------------------68. Folds a piece of paper in thirds to put in an envelope

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104 Domain (Eigenvalue) Loading Items Social Use of Language (4.2) .58 .57 .55 .47 .43 .40 .51 .50 .45 .41 .40 .40 78. Understands subtle jokes 80. Recognizes when someone is asking a question 79. Understands that they are being teased 94. Stays on topic when telling a story or explaining something 81. Recognizes when spouse or loved one is upset 82. Understands obvious humor ---------------------------------------------------------------------98. Jumps to a topic unrelated to the conversation 97. Blurts out something off topic during a conversation 107. Talks at the wrong time 89. Uses flat tone of voice when should be expressing anger or happiness 85. Tone of voice does not indicate that a minor problem has occurred 90. Facial expression does not match the conversation Emotional Function (4.9) .65 .59 .56 .54 .50 .44 .43 .40 .46 .46 .44 143. Overreacts to frustrating situations . 148. Emotions swing among happy, sad, and angry 149. Has angry or tearful outbursts for no apparent reason | 142. Blurts out things that are offensive to others 144. Gets upset with a change of routine 138. Asks embarrassing questions or makes hurtful or inappropriate comments 147. Gets upset with new situations 120. Feels or shows a different intensity of emotion than before the stroke ---------------------------------------------------------------------136. Acknowledges when someone is crying or shouting 134. Shows an emotional response to a sad movie or story 131. Reacts when people are visibly upset.

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105 Domain (Eigenvalue) Loading Items Attention (2.6) .66 .61 .52 .48 .53 .42 167. Correctly writes down a message from an answering machine or person on the phone 159. Selects meal items from a menu 160. Copies information correctly 168. Locates a phone number or address in the telephone book --------------------------------------------------------------------172. Watches TV without being distracted by people talking 173. Talks with a person while the TV is on. Executive Function (5.7) .66 .65 .59 .57 .56 .55 .51 .43 .42 .42 .50 .44 .41 .41 .41 207. Easy thinking tasks seem difficult and require a lot of effort 213. Makes more mistakes during a long thinking task 214. Gets slower and slower during a long th inking task 206. Feels tired or exhausted after working on a short thinking task | 215. Avoids a leisure activity because it takes too much mental energy 208. Avoids things that involve mental energy 192. Makes careless errors during a new activity 191. Makes careless errors in daily tasks 201. Takes a long time to come up with an answer to a question after it is asked 212. Falls asleep in the middle of a thinking task ---------------------------------------------------------------------178. Fills free time with activities without being told 182. Readily switches from one activity to another 199. Responds to simple requests without being asked several times 184. Stops an activity and starts a new activity without being told 185. Plans a common daily activity Memory (3.2) .69 .66 .52 .49 .45 .52 .51 .42 243. Says home address correctly 244. Names the current President 237. Sa 242. Says home phone number correctly 240. Says age correctly ---------------------------------------------------------------------218. Recalls specific activities from last birthday or vacation 220. Recalls activities or events from one month ago 221. Recalls activities or events from several months ago

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106 APPENDIX E MFC STROKE PAPER AND PEN CIL FIELD TEST ITEM P OOL FOR PATIENT I. LANGUAGE 1. I turn my head in direction of speaker when my name is called. Never Sometimes Often Always N/A 2. I respond to simple yes or no questions either by nodding, gesturing, or speaking. Never Sometimes Often Always N/A 3. I follow simple directions when asked (for example, "Hand me the cup."). Never Sometimes Often Always N/A 4. I follow 2 step directions when asked (for example, "Pick up the paper and throw it away."). Never Sometimes Often Always N/A 5. I follow multiple step directions when asked (for example, I am able to follow directions to find a location or place). Never Sometimes Often Always N/A 6. I follow a simple conversation by appropriately nodding, smiling, gesturing, or commenting. Never Sometimes Often Always N/A 7. I follow a conversation in a distracting environment by appropriately nodding, smiling, gesturing, or commenting. Never Sometimes Often Always N/A 8. I answer questions correctly about complex information (for example, medical history or the plot of a movie). Never Sometimes Often Always N/A 9. I use single words or everyday phrases (for example, "Hi," "Bye," or "How are you?"). Never Sometimes Often Always N/A 10. I use more than one word to express needs (for example, "drink coffee," "eat lunch," or "tired sleep"). Never Sometimes Often Always N/A 11. I speak in short sentences (for example, "It's time to go" or "I feel sick"). Never Sometimes Often Always N/A 12. I find the right words to get ideas across with few mistakes. Never Sometimes Often Always N/A 13. I carry on a conversation without mistakes. Never Sometimes Often Always N/A II. READING & WRITING 1. I read familiar words (for example, my name, address, or neighborhood street signs). Never Sometimes Often Always N/A 2. I read the menu in a restaurant. Never Sometimes Often Always N/A 3. I read signs in a store or hospital. Never Sometimes Often Always N/A

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107 4. I read titles of articles in the daily newspaper. Never Sometimes Often Always N/A 5. I read a personal letter that is from a relative or friend. Never Sometimes Often Always N/A 6. I read a complete article in the daily newspaper or magazine. Never Sometimes Often Always N/A 7. I read a book. Never Sometimes Often Always N/A 8. I read complex information (for example, insurance documents or papers that come with medicine). Never Sometimes Often Always N/A 9. I write my name and address. Never Sometimes Often Always N/A 10. I write a short list (for example, a shopping list). Never Sometimes Often Always N/A 11. I write a short note (for example, a phone message or brief instruction). Never Sometimes Often Always N/A 12. I complete a business form (for example, credit card application, catalog order form, or medical form). Never Sometimes Often Always N/A 13. I write a brief letter (for example, a postcard, personal letter, or e mail). Never Sometimes Often Always N/A 14. I write more than one paragraph (for example, a long letter, story, or report). Never Sometimes Often Always N/A III. NUMERICAL CALCULATION 1. I recognize numbers (for example, I point to my phone number or birthdate on a form). Never Sometimes Often Always N/A 2. I understand what numbers mean (for example, I tell time using a digital clock). Never Sometimes Often Always N/A 3. I copy numbers (for example, the amount from a bill to a checkbook). Never Sometimes Often Always N/A 4. I add and subtract small numbers (for example, to balance a checkbook). Never Sometimes Often Always N/A 5. I correctly pay for an item with exact change. Never Sometimes Often Always N/A 6. I correctly make change. Never Sometimes Often Always N/A 7. I correctly divide restaurant bill for separate payments among diners. Never Sometimes Often Always N/A 8. I correctly calculate amount of tip for the waitress or waiter. Never Sometimes Often Always N/A

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108 9. I correctly measure an amount (for example, 1/2 cup or 1/4 inch). Never Sometimes Often Always N/A IV. LIMB PRAXIS 1. I wave hello or good bye. Never Sometimes Often Always N/A 2. I am clumsy when using tools (for example, eating utensils, pencil, or pen). Never Sometimes Often Always N/A 3. I use the wrong eating utensil (for example, I try to eat cereal with a knife or try to cut meat with a spoon). Never Sometimes Often Always N/A 4. I use incorrect cooking tools (for example, I use a knife for mixing batter or use a spoon to flip an egg). Never Sometimes Often Always N/A 5. I choose the right utensil but use it in the wrong way (for example, I try to eat soup with a spoon upside down or try to cut with the dull edge of a knife). Never Sometimes Often Always N/A 6. I choose the right kitchen tool but use it in the wrong way (for example, I use a whisk outside the bowl). Never Sometimes Often Always N/A 7. I choose the right grooming tool but use it in the wrong way (for example, I use a brush handle to brush my hair or use the wrong end of an electric razor). Never Sometimes Often Always N/A 8. I use the incorrect grooming tool (for example, I use a comb to brush my teeth or toothbrush to comb my hair). Never Sometimes Often Always N/A 9. I choose the incorrect tool for the job (for example, I choose a saw to pound a nail or choose a spatula to beat eggs). Never Sometimes Often Always N/A 10. I choose the right tool for the job but use in the wrong way (for example, I try to hammer a nail upside down). Never Sometimes Often Always N/A V. VISUAL SPATIAL FUNCTION 1. I recognize my own face in the mirror. Never Sometimes Often Always N/A 2. I recognize faces of close family members (for example, spouse or children). Never Sometimes Often Always N/A 3. I recognize faces of neighbors, co workers, hairdresser, or pastor/minister. Never Sometimes Often Always N/A 4. I recognize the face of a person I just met (for example, new therapist, grocery clerk, or delivery person). Never Sometimes Often Always N/A

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109 5. I move my eyes or turn my head to left side in response to person entering room or the phone ringing. Never Sometimes Often Always N/A 6. I read words on left side of a menu, newspaper, or book. Never Sometimes Often Always N/A 7. I write or draw on left side of paper. Never Sometimes Often Always N/A 8. I eat food on left side of plate or tray. Never Sometimes Often Always N/A 9. I look at left side of clock or use left side controls on radio or TV. Never Sometimes Often Always N/A 10. I dress or groom the left side of my body. Never Sometimes Often Always N/A 11. I bump into doorways on left side. Never Sometimes Often Always N/A 12. My paralyzed limb hangs over the wheelchair arm. Never Sometimes Often Always N/A 13. I find my way around my house. Never Sometimes Often Always N/A 14. I find my way around family or friends' house. Never Sometimes Often Always N/A 15. I find my way around grocery store to locate items. Never Sometimes Often Always N/A 16. I get lost when driving or walking around my neighborhood. Never Sometimes Often Always N/A 17. I get lost in a new setting (for example, new building, hospital, house, or city). Never Sometimes Often Always N/A 18. I use a map or directory to find a new location. Never Sometimes Often Always N/A 19. I reach out directly and grasp an object (for example, I pick up a cup without reaching around for it). Never Sometimes Often Always N/A 20. I locate a particular item on the first try (for example, I go to the correct drawer to get an article of clothing or kitchen utensil). Never Sometimes Often Always N/A 21. I use a mouse to click on a computer screen. Never Sometimes Often Always N/A 22. I fold a piece of paper in thirds to put in an envelope. Never Sometimes Often Always N/A 23. I point to a specific area of text on a page (for example, a phone number in the phone book or a section of a menu or bill). Never Sometimes Often Always N/A

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110 24. I get a specific book off a bookshelf. Never Sometimes Often Always N/A 25. I make an entry on the correct line of a form (for example, in a checkbook). Never Sometimes Often Always N/A 26. I point to a location on a map or directory. Never Sometimes Often Always N/A 27. I stack items according to shape and size (for example, dishes, containers, books, or tools in a case). Never Sometimes Often Always N/A 28. I build or construct things (for example, I make scrapbooks, build bird houses, or assemble puzzles). Never Sometimes Often Always N/A 29. I draw a simple sketch (for example, a stick figure of a person or a flower). Never Sometimes Often Always N/A 30. I copy a chart from a book (for example, a chart of facts or diagram from a text book). Never Sometimes Often Always N/A 31. I draw a simple map. Never Sometimes Often Always N/A VI. SOCIAL USE OF LANGUAGE 1. I understand subtle jokes (for example, a play on words or witty remark). Never Sometimes Often Always N/A 2. I understand when I am being teased. Never Sometimes Often Always N/A 3. I recognize when someone is asking a question (for example, I recognize intonation). Never Sometimes Often Always N/A 4. I recognize when my spouse or loved one is upset. Never Sometimes Often Always N/A 5. I understand obvious humor (for example, "a pie in the face"). Never Sometimes Often Always N/A 6. I understand why people are crying at a tragic event (for example, a car accident or death). Never Sometimes Often Always N/A 7. I misunderstand the intent of the person who is speaking (for example, I do not recognize when someone makes a joke or uses sarcasm). Never Sometimes Often Always N/A 8. My tone of voice does not indicate that a minor problem has occurred (for example, spilling a drink on some papers). Never Sometimes Often Always N/A 9. My tone of voice does not indicate an emotion (for example, anger, urgency, or fear). Never Sometimes Often Always N/A 10. My tone of voice does not indicate that a question is being asked. Never Sometimes Often Always N/A

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111 11. I sound rude or demanding when making a request. Never Sometimes Often Always N/A 12. I use a flat tone of voice when I should be expressing anger or happiness. Never Sometimes Often Always N/A 13. My facial expression does not match the conversation (for example, I smile too much during a serious conversation or look angry when saying something nice). Never Sometimes Often Always N/A 14. I stay on topic while participating in a short conversation. Never Sometimes Often Always N/A 15. I make a relevant comment during a conversation. Never Sometimes Often Always N/A 16. I smoothly change to a new topic during a conversation. Never Sometimes Often Always N/A 17. I stay on topic when telling a story or explaining something. Never Sometimes Often Always N/A 18. I leave out an important piece of information during a conversation. Never Sometimes Often Always N/A 19. I get stuck on a topic during a conversation (for example, I keep talking about the same thing). Never Sometimes Often Always N/A 20. I blurt out something off topic during a conversation. Never Sometimes Often Always N/A 21. I jump to a topic unrelated to the conversation. Never Sometimes Often Always N/A 22. I tell life events or story in the correct order (for example, describing education or work history). Never Sometimes Often Always N/A 23. I use appropriate eye contact when having a conversation. Never Sometimes Often Always N/A 24. I begin to answer open ended questions within Never Sometimes Often Always N/A 25. I have a conversation with more than one person. Never Sometimes Often Always N/A 26. I allow others to take a turn in a conversation (for example, I give another person a chance to talk). Never Sometimes Often Always N/A 27. I show interest in what other people are saying (for example, by commenting or nodding). Never Sometimes Often Always N/A Never Sometimes Often Always N/A 29. I go on and on without giving another person a chance to talk. Never Sometimes Often Always N/A

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112 30. I talk at the wrong time (for example, I talk when I should be listening). Never Sometimes Often Always N/A 31. I turn toward a person when speaking to him/her. Never Sometimes Often Always N/A 32. I walk away from a conversation before it is finished. Never Sometimes Often Always N/A VII. EMOTIONAL FUNCTION 1. I recognize that I had a stroke. Never Sometimes Often Always N/A 2. I recognize that I have problems resulting from a stroke (for example, trouble talking, walking, thinking, or remembering things). Never Sometimes Often Always N/A 3. I recognize that I need assistance for problems caused by a stroke. Never Sometimes Often Always N/A 4. I attempt tasks that involve thinking skills beyond my ability (for example, I try to manage finances alone when I really need help). Never Sometimes Often Always N/A 5. I attempt to do physical things that I cannot do (for example, I try to get dressed when needing physical help). Never Sometimes Often Always N/A 6. I do not know why things are difficult since having a stroke. Never Sometimes Often Always N/A 7. I blame others for problems or mistakes. Never Sometimes Often Always N/A 8. I demonstrate an understanding of my own abilities (for example, I know what I can and cannot do, such as driving, returning to school/work, or cooking). Never Sometimes Often Always N/A 9. I am aware of a problem in functioning, but I believe it is due to something other than the stroke (for example, I make excuses or say that's how I've always been). Never Sometimes Often Always N/A 10. I attempt to do something that would result in harm to myself or others (for example, I cook alone when I need supervision or try to drive with visual problems). Never Sometimes Often Always N/A 11. I feel or show a different intensity of emotion than before the stroke (for example, my emotions seem to be much stronger or to be lacking or "flat"). Never Sometimes Often Always N/A 12. I get as much done during the day as I had planned. Never Sometimes Often Always N/A 13. I see a job through to the end. Never Sometimes Often Always N/A

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113 14. I show interest in trying new things (for example, starting a new hobby or learning something new). Never Sometimes Often Always N/A 15. I have trouble making plans for the future. Never Sometimes Often Always N/A 16. I get started on things that are important to me. Never Sometimes Often Always N/A 17. I show concern about impairments or challenges (for example, I am aware of deficits). Never Sometimes Often Always N/A 18. I show interest in getting together with friends or extended family. Never Sometimes Often Always N/A 19. I show emotion when something very exciting or bad happens. Never Sometimes Often Always N/A 20. I s how interest in doing things. Never Sometimes Often Always N/A 21. I pick up on subtle displays of emotion (for example, when someone rolls their eyes or shrugs). Never Sometimes Often Always N/A 22. I react when people are visibly upset (for example, I ask "Are you ok?" when someone is crying). Never Sometimes Often Always N/A 23. I show concern when someone is talking about their problems (for example, I offer words of support). Never Sometimes Often Always N/A 24. I make demands without considering the other person's feelings (for example, I ask someone who is crying to do something). Never Sometimes Often Always N/A 25. I show an emotional response to a sad movie or story (for example, I become tearful or upset). Never Sometimes Often Always N/A 26. I recognize another person's point of view. Never Sometimes Often Always N/A 27. I acknowledge when someone is crying or shouting. Never Sometimes Often Always N/A 28. I show an emotional response that does not match the situation (for example, I show no response to bad news or laugh inappropriately). Never Sometimes Often Always N/A 29. I ask embarrassing questions or make hurtful or inappropriate comments. Never Sometimes Often Always N/A 30. I become tearful easily. Never Sometimes Often Always N/A 31. I stop an activity and start a new activity without getting upset (for example, I stop watching TV and come to eat dinner). Never Sometimes Often Always N/A 32. I accept constructive criticism without losing my temper. Never Sometimes Often Always N/A

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114 33. I blurt out things that are offensive to others (for example, I curse or make sexual comments). Never Sometimes Often Always N/A 34. I overreact to frustrating situations (for example, tool does not work or someone takes parking place). Never Sometimes Often Always N/A 35. I get upset with a change of routine. Never Sometimes Often Always N/A 36. I accept help without losing my temper. Never Sometimes Often Always N/A arguing. Never Sometimes Often Always N/A 38. I get upset with new situations (for example, change of nurse, therapist, or room). Never Sometimes Often Always N/A 39. My emotions swing among happy, sad, and angry. Never Sometimes Often Always N/A 40. I have angry or tearful outbursts for no apparent reason. Never Sometimes Often Always N/A VIII. ATTENTION 1. I correctly answer yes or no questions about Never Sometimes Often Always N/A 2. I use short sentences that make sense. Never Sometimes Often Always N/A 3. I pay attention to an hour long TV program. Never Sometimes Often Always N/A 4. I read 30 minutes without taking a break. Never Sometimes Often Always N/A 5. I listen to a 15 30 minute speech or presentation quietly and with focus (for example, religious service or class lecture). Never Sometimes Often Always N/A 6. I go directly from my room to another room without wandering (for example, dining room or therapy room). Never Sometimes Often Always N/A 7. I turn my eyes in the direction of someone entering the room. Never Sometimes Often Always N/A 8. I wave or nod to someone who enters the room. Never Sometimes Often Always N/A 9. I greet someone who enters the room. Never Sometimes Often Always N/A 10. I select meal items from a menu. Never Sometimes Often Always N/A

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115 11. I copy information correctly (for example, daily schedule or medical information). Never Sometimes Often Always N/A 12. I answer the ringing phone. Never Sometimes Often Always N/A 13. I participate in a therapy session for 30 minutes with a rest break. Never Sometimes Often Always N/A 14. I participate in a therapy session for 30 minutes without a rest break. Never Sometimes Often Always N/A 15. I complete self care activities without getting distracted (for example, brushing teeth or getting dressed). Never Sometimes Often Always N/A 16. I complete an activity in a busy or distracting environment without stopping. Never Sometimes Often Always N/A 17. I complete a meal while talking with someone. Never Sometimes Often Always N/A 18. I correctly write down a message from an answering machine or person on the phone. Never Sometimes Often Always N/A 19. I locate a phone number or address in the telephone book. Never Sometimes Often Always N/A 20. I return to an activity without a reminder after a short interruption. Never Sometimes Often Always N/A 21. I stop in the middle of a task when distracted (for example, by someone talking). Never Sometimes Often Always N/A 22. I have a conversation in a noisy environment (for example, cafeteria or therapy room). Never Sometimes Often Always N/A 23. I watch TV without being distracted by people talking. Never Sometimes Often Always N/A 24. I talk with a person while the TV is on. Never Sometimes Often Always N/A 25. I pay attention to the wrong conversation (for example, I listen to nearby talking). Never Sometimes Often Always N/A IX. EXECUTIVE FUNCTION 1. I start an activity automatically (for example, I start to eat when given food or wash my face when given a wash cloth). Never Sometimes Often Always N/A 2. I respond to simple requests in a timely manner (for example, I sit up upon request or eat on request). Never Sometimes Often Always N/A 3. I start an activity without being told (for example, exercise program, chores, or housework). Never Sometimes Often Always N/A

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116 4. I fill free time with activities without being told. Never Sometimes Often Always N/A 5. I provide at least one solution to a problem. Never Sometimes Often Always N/A 6. I try a different approach to a problem when the first one does not work (for example, when a drain cleaner does not work, I call a plumber). Never Sometimes Often Always N/A 7. I plan a big project (for example, I arrange a trip or home improvement). Never Sometimes Often Always N/A 8. I readily switch from one activity to another (for example, I stop watching TV to begin dressing). Never Sometimes Often Always N/A 9. I say the same thing over and over (for Never Sometimes Often Always N/A 10. I stop an activity and start a new activity without being told (for example, I stop watching TV to do a chore). Never Sometimes Often Always N/A 11. I plan a common daily activity (for example, I gather items needed for dressing or grooming). Never Sometimes Often Always N/A 12. I plan ahead in order to get to an appointment on time. Never Sometimes Often Always N/A 13. I start a task early enough to get it done (for example, I start to get ready for school, work, or appointment in order to arrive on time). Never Sometimes Often Always N/A 14. I break a job down into smaller parts (for example, steps for cooking a meal or organizing the garage). Never Sometimes Often Always N/A 15. I organize an activity several days in advance (for example, I plan a trip or plan holiday activities). Never Sometimes Often Always N/A 16. I keep my personal area organized (for example, I put things away or straighten things up). Never Sometimes Often Always N/A 17. I make careless errors in daily tasks (for example, I miss a button or forget to put toothpaste on toothbrush). Never Sometimes Often Always N/A 18. I make careless errors during a new activity (for example, cooking or craft project). Never Sometimes Often Always N/A 19. I readily change behaviors when an error is pointed out. Never Sometimes Often Always N/A 20. I catch my own mistakes while working on a task. Never Sometimes Often Always N/A 21. I seek help when needed. Never Sometimes Often Always N/A

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117 22. I follow safety rules (for example, looking both ways before crossing street or not opening doors to strangers). Never Sometimes Often Always N/A 23. I respond appropriately to dangerous situations (for example, I call for help if injured or turn heat down if a pot is boiling over). Never Sometimes Often Always N/A 24. I try to do an activity before having the ability to do it (for example, walking, cooking, or driving). Never Sometimes Often Always N/A 25. I respond to simple requests without being asked several times (for example, "Close your eyes" or "Look at me"). Never Sometimes Often Always N/A 26. I respond to a question without being asked several times (for example, "What do you want to Never Sometimes Often Always N/A 27. I take a long time to come up with an answer to a question after it is asked. Never Sometimes Often Always N/A 28. I follow an automated phone menu that contains instructions or choices (for example, "Press 1 for an operator"). Never Sometimes Often Always N/A 29. I take things literally (for example, I leave the room when someone jokingly says, "Oh, get out of here!"). Never Sometimes Often Always N/A 30. I complete a new routine in the allowed time (for example, I complete a therapy activity by the end of the session). Never Sometimes Often Always N/A 31. I keep up the pace required of therapy, school, or work. Never Sometimes Often Always N/A 32. I feel tired or exhausted after working on a short thinking task (for example, after paying a few bills or making a grocery list). Never Sometimes Often Always N/A 33. Easy thinking tasks seem difficult to me and require a lot of effort. Never Sometimes Often Always N/A 34. I avoid things that involve mental energy (for example, balancing a checkbook or attending a meeting). Never Sometimes Often Always N/A 35. I have trouble getting up the energy to start a project or chore. Never Sometimes Often Always N/A 36. I have trouble maintaining energy to complete a thinking task (for example, reading or doing a crossword puzzle). Never Sometimes Often Always N/A 37. I have the mental energy to do basic activities (for example, getting dressed or making a phone call). Never Sometimes Often Always N/A 38. I fall asleep in the middle of a thinking task (for example, during reading or a meeting). Never Sometimes Often Always N/A

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118 39. I make more mistakes during a long thinking task (for example, balancing a checkbook or writing a letter). Never Sometimes Often Always N/A 40. I get slower and slower during a long thinking task (for example, balancing a checkbook or writing a letter). Never Sometimes Often Always N/A 41. I avoid a leisure activity because it takes too much mental energy (for example, reading or doing crossword puzzles). Never Sometimes Often Always N/A X. MEMORY 1. I recall what I did before the stroke (for example, job, school, or homemaking). Never Sometimes Often Always N/A 2. I recall birthdays, holidays, and anniversaries. Never Sometimes Often Always N/A 3. I recall specific activities from last birthday or vacation. Never Sometimes Often Always N/A 4. I recall activities or events from one week ago. Never Sometimes Often Always N/A 5. I recall activities or events from one month ago. Never Sometimes Often Always N/A 6. I recall activities or events from several months ago. Never Sometimes Often Always N/A 7. I recall childhood memories (for example, school, pets, and friends). Never Sometimes Often Always N/A 8. I recall activities done earlier in the day (for example, I remember what I had for breakfast or visiting the doctor). Never Sometimes Often Always N/A 9. I describe the steps of a simple activity (for example, making a sandwich). Never Sometimes Often Always N/A 10. I complete steps of a simple activity (for example, washing a car). Never Sometimes Often Always N/A 11. I recall the information given at a previous appointment. Never Sometimes Often Always N/A 12. I recall the story line in a book from one reading to the next. Never Sometimes Often Always N/A 13. I recall how to use simple equipment (for example, using call button to call nurse or turning on TV). Never Sometimes Often Always N/A 14. I recall a simple therapy routine (for example, exercise program or using memory book). Never Sometimes Often Always N/A 15. I recall simple routines (for example, switching laundry from washer to dryer or locking the door when leaving the house). Never Sometimes Often Always N/A

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119 16. I recall more than one appointment in a single day (for example, multiple health care appointments or social activities). Never Sometimes Often Always N/A 17. I recall a visit by a familiar person from the previous day (for example, a friend or family member). Never Sometimes Often Always N/A 18. I recall where to find something when it is not put in its usual place (for example, looking for keys). Never Sometimes Often Always N/A 19. I recall where the car is parked in the mall or grocery store parking lot. Never Sometimes Often Always N/A 20. I recall whether or not medicine was taken that day. Never Sometimes Often Always N/A 21. I say my name correctly when asked. Never Sometimes Often Always N/A (for example, wife, husband, brother, or sister). Never Sometimes Often Always N/A 23. I answer correctly when asked for current location (for example, "Where are you right now?"). Never Sometimes Often Always N/A 24. I correctly report why I am/was in hospital. Never Sometimes Often Always N/A 25. I say my age correctly. Never Sometimes Often Always N/A 26. I say the current year correctly. Never Sometimes Often Always N/A 27. I say my home phone number correctly. Never Sometimes Often Always N/A 28. I say my home address correctly. Never Sometimes Often Always N/A 29. I name the current President. Never Sometimes Often Always N/A

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120 LIST OF REFERENCES 1. Wright BD, Linacre JM, Gustafson J, Martin Lof P. Reasonable mean square fit values. Rasch measurement transactions 1994;8:370. 2. Allaire JC, Marsiske M. Everyday cognition: age and intellectual ability correlates. Psychology and Aging; Psychology and Aging 1999;14:627. 3. Arbuthnott K, Frank J. Trail making test, part B as a measure of executive control: validation using a set switching paradigm. Journal of Clinical and Experimental Neuropsychology 2000;22:518 528. 4. Baltes PB, Cornelius SW, Spiro A Nesselroade JR, Willis SL. Integration versus differentiation of fluid/crystallized intelligence in old age. Developmental Psychology 1980;16:625 635. 5. Berg KO, Maki BE, Williams JI, Holliday PJ, Wood Dauphinee SL. Clinical and laboratory measures of postural balance in an elderly population. Archives of physical medicine and rehabilitation 1992;73:1073. 6. Blom G. Statistical elements and transformed beta variables. 1958 7. Bond T, Fox C. Applying the Rasch model: Fundamental measurement in the human sciences Lawrence Erlbaum; 2007. 8. Bond TG, Fox, C. M. Applying the Rasch Model: Fundamental Measurement in the Human Sciences Mahwah, New Jersey: Lawrence Erlbaum Associates; 2007. 9. Caplan B, Moelter S. Stroke. In: Frank RG, Elliott TR, eds. Handbook of Rehabilitation Psychology Washington, DC: American Psychological Association; 2000:75 108. 10. Carroll JB. The three stratum theory of cognitive abilities. 1997. 11. Carroll JB. The higher stratum structure of cognitive abilities: Current evid ence supports g and about ten broad factors. The scientific study of general intelligence: Tribute to Arthur R Jensen 2003;5 21. 12. Cattell RB. Theory of fluid and crystallized intelligence: A critical experiment. Journal of educational psychology 1963; 54:1. 13. Cattell RB. The scree test for the number of factors. Multivariate behavioral research 1966;1:245 276.

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121 14. Cella D, Riley W, Stone A et al. The Patient Reported Outcomes Measurement Information System (PROMIS) developed and tested its first wave of adult self reported health outcome item banks: 2005 2008. J Clin Epidemiol 2010;63:1179 1194. 15. Conrad KJ, Wright BD, Mcknight P, Mcfall M, Fontana A, Rosenheck R. Comparing traditional and Rasch analyses of the Mississippi PTSD scale: Revealing lim itations of reverse scored items. Journal of Applied Measurement 2004;5:15 30. 16. Cook DA, Beckman TJ. Current concepts in validity and reliability for psychometric instruments: theory and application. The American journal of medicine 2006;119:166 e16. 17. Coster WJ, Haley SM, Ludlow LH, Andres PL, Ni PS. Development of an applied cognition scale to measure rehabilitation outcomes. Archives of physical medicine and rehabilitation 2004;85:2030 2035. 18. Cournan M. Use of the functional independence measu re for outcomes measurement in acute inpatient rehabilitation. Rehabilitation Nursing 2011;36:111 117. 19. De Frias CM, Lvdn M, Lindenberger U, Nilsson L G. Revisiting the dedifferentiation hypothesis with longitudinal multi cohort data. Intelligence 2 007;35:381 392. 20. Delis DC, Kaplan E, Kramer JH. Delis Kaplan executive function system (D KEFS) Psychological Corporation; 2001. 21. Devellis RF. Classical Test Theory. Medical Care 2006;44:S50 S59. 22. Diehl M, Marsiske M, Horgas A, Rosenberg A, Sacz ynski J, Willis S. The Revised Observed Tasks of Daily Living: A Performance Based Assessment of Everyday Problem Solving in Older Adults. J Appl Gerontol 2005;24:211 230. 23. Donovan NJ, Kendall DL, Heaton SC, Kwon S, Velozo CA, Duncan PW. Conceptualizin g functional cognition in stroke. Neurorehabilitation and Neural Repair 2008;22:122. 24. Duncan PW, Horner RD, Reker DM et al. Adherence to postacute rehabilitation guidelines is associated with functional recovery in stroke. Stroke 2002;33:167 178. 25. Duncan PW, Lai SM, Keighley J. Defining post stroke recovery: implications for design and interpretation of drug trials. Neuropharmacology 2000;39:835.

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123 40. Corp. IBM. IBM SPSS Statistics for Windows Armonk, NY: 2012. 41. Jette DU, Halbert J, Iverson C, Miceli E, Shah P. Use of Standardized Outcome Measures in Physical Therapist Practice: Perceptions and Applications. Physical Therapy 2009;89:125 135. 42. Kaiser HF. The application of electronic computers to factor analysis. Educational and psychological measurement 1960. 43. Kane R. Understanding health care outcomes research Jones & B artlett Learning; 2008. 44. Keith RA, Granger CV, Hamilton BB, Sherwin FS. The functional independence measure: a new tool for rehabilitation. Advances in clinical rehabilitation 1987;1:6. 45. Kelley T, Ebel R, Linacre J. Item discrimination indices. Rasc h Measurement Transactions 2002;16:883 884. 46. Kirasic KC, Allen GL, Dobson SH, Binder KS. Aging, cognitive resources, and declarative learning. Psychology and Aging 1996;11:658. 47. Kollen B, Kwakkel G, Lindeman E. Functional recovery after stroke: a r eview of current developments in stroke rehabilitation research. Reviews on Recent Clinical Trials 2006;1:75 80. 48. Kramer A, Holthaus D. Uniform patient assessment for post acute care. Aurora: Division of Health Care Policy and Research University of Co lorado at Denver and Health Sciences Center 2006. 49. Lamberty GJ, Putnam SH, Chatel DM, Bieliauskas LA, Adams KM. A Preliminary Report. Cognitive and Behavioral Neurology 1994;7:230 234. 50. Larson EB, Kirschner K, Bode R, Heinemann A, Goodman R. Constr uct and predictive validity of the Repeatable Battery for the Assessment of Neuropsychological Status in the evaluation of stroke patients. Journal of Clinical and Experimental Neuropsychology 2005;27:16 32. 51. Larson EB, Kirschner K, Bode RK, Heinemann AW, Clorfene J, Goodman R. Brief cognitive assessment and prediction of functional outcome in stroke. Topics in stroke rehabilitation 2003;9:10 21. 52. Lehto JE, Juujrvi P, Kooistra L, Pulkkinen L. Dimensions of executive functioning: Evidence from children. British Journal of Developmental Psychology 2003;21:59 80. 53. J.M. L. Unidimensional Models in a Multidimensional World. Rasch Measurement Transactions 2009;23:1209.

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124 54. Linacre J. a href="http://www.ncbi. nlm.nih.gov/pubmed/20485233">Two perspectives on the application of Rasch models.. European journal of 2010. 55. Linacre J. Oregon: Winsteps.Com. Winsteps Rasch measurement computer program. 2012. 56. Linacre JM. Detecti ng multidimensionality: which residual data type works best? Journal of outcome measurement 1998;2:266 283. 57. Linacre JM. Optimizing rating scale category effectiveness. Journal of applied measurement 2002;3:85 106. 58. Linacre JM. Winsteps Rasch meas urement computer program User's Guide. 2012 59. Linacre JM. Sample size and item calibration stability. Rasch Measurement Transactions 1994;7:328. 60. Little TD, Cunningham WA, Shahar G, Widaman KF. To parcel or not to parcel: Exploring the question, weighing the merits. Structural Equation Modeling 2002;9:151 173. 61. Magasi S, Ryan G, Revicki D et al. Content validity of patient reported outcome measu res: perspectives from a PROMIS meeting. Quality of Life Research 2012;21:739 746. 62. Mcgrew KS. The Cattell Horn Carroll Theory of Cognitive Abilities: Past, Present, and Future. 2005. 63. Mcphail S, Beller E, Haines T. Two perspectives of proxy reporti ng of health related quality of life using the Euroqol 5D, an investigation of agreement. Medical care 2008;46:1140 1148. 64. Miyake A, Friedman NP, Emerson MJ, Witzki AH, Howerter A, Wager TD. The unity and diversity of executive functions and their cont ributions to complex Cognitive psychology 2000;41:49 100. 65. Mooney S, Hasssanein TI, Hilsabeck RC et al. Utility of the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) in patie nts with end stage liver disease awaiting liver transplant. Archives of clinical neuropsychology 2007;22:175 186. 66. Research plan for the national center for medical rehabilitation research. 1993, National Institutes of Health

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127 BIOGRAPHICAL SKETCH Kathleen Berger, PT graduated with her Bachelor of Science in physical therapy in 1984 from Northwestern University. Her clinical experience has been divided between the fiel ds of geriatrics and pediatrics Her earlier work included employment in the home care setting, skilled nursing facility, and rehabilitation c enters with persons with stroke. More recently, her work has focused on persons with developmental disability. After her son was diagnosed with a seizure disorder and autism in 1990, she was pushed into understand ing more about autism. Then, after founding and directing a therapy intensive respite program for children with autism and their families, Kathleen returned to graduate school to become competent to do research to understand autism better, especially persons with nonverbal autism. Kathle en completed her Master of Science in psychology in 2010, and her PhD in rehabilitation science from the U niversity of Florida in 2013.