Using the Rasch Model to Develop a Measure of Participation Capturing the Full Range of Participation Characteristics for the Patients with Hand Injuries

Objective The purpose of this paper was to report on the first step in the development of a new instrument to measure participation including the full range of its characteristics. Methods The 30-item participation behavior questionnaire (PBQ) was developed from four main sources (a literature review of the theatrical basis of participation, available participation measures, and interviews with patients and experts about participation). Item selection and the reliability and validity of the measure were explored using Rasch measurement modeling for analysis. Participants A total of 404 individuals referred to rehabilitation after hand, wrist, or upper extremity surgery to reduce impairment from trauma, at least 2 months post-injury. Results An initial pool of 100 items; reflecting 14 characteristics of participation was initially reduced to 91 items after review by 15 participation experts and then further reduced to 30 items by three rounds of Rasch analysis removing misfitting items. The final PBQ has a person reliability of 0.91 with separation of 3.22, indicating it can reliably differentiate four levels of participation. There are no misfitting items and the instrument is unidimensional. All 14 characteristics of participation were retained in the PBQ, and none of the 30 items refer specifically to upper extremity issues. Conclusion The 30 participation behavior items of the PBQ show promise of being a psychometrically sound measure of participation. Further research is needed to validate the PBQ in samples of people with a range of other disabilities.

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A Rasch-Validated Version of the Upper Extremity Functional Index for Interval-Level Measurement of Upper Extremity Function

Physical Therapy ◽

10.2522/ptj.20130041 ◽

2013 ◽

Vol 93 (11) ◽

pp. 1507-1519 ◽

Cited By ~ 13

Author(s):

Clayon B. Hamilton ◽

Bert M. Chesworth

Keyword(s):

Differential Item Functioning ◽

Upper Extremity ◽

Rasch Model ◽

Rasch Analysis ◽

Measurement Properties ◽

Functional Index ◽

Extremity Function ◽

Item Functioning ◽

Upper Extremity Function ◽

The Rasch Model

Background The original 20-item Upper Extremity Functional Index (UEFI) has not undergone Rasch validation. Objective The purpose of this study was to determine whether Rasch analysis supports the UEFI as a measure of a single construct (ie, upper extremity function) and whether a Rasch-validated UEFI has adequate reproducibility for individual-level patient evaluation. Design This was a secondary analysis of data from a repeated-measures study designed to evaluate the measurement properties of the UEFI over a 3-week period. Methods Patients (n=239) with musculoskeletal upper extremity disorders were recruited from 17 physical therapy clinics across 4 Canadian provinces. Rasch analysis of the UEFI measurement properties was performed. If the UEFI did not fit the Rasch model, misfitting patients were deleted, items with poor response structure were corrected, and misfitting items and redundant items were deleted. The impact of differential item functioning on the ability estimate of patients was investigated. Results A 15-item modified UEFI was derived to achieve fit to the Rasch model where the total score was supported as a measure of upper extremity function only. The resultant UEFI-15 interval-level scale (0–100, worst to best state) demonstrated excellent internal consistency (person separation index=0.94) and test-retest reliability (intraclass correlation coefficient [2,1]=.95). The minimal detectable change at the 90% confidence interval was 8.1. Limitations Patients who were ambidextrous or bilaterally affected were excluded to allow for the analysis of differential item functioning due to limb involvement and arm dominance. Conclusion Rasch analysis did not support the validity of the 20-item UEFI. However, the UEFI-15 was a valid and reliable interval-level measure of a single dimension: upper extremity function. Rasch analysis supports using the UEFI-15 in physical therapist practice to quantify upper extremity function in patients with musculoskeletal disorders of the upper extremity.

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Evaluation of Hajj Instrument (HAJI) Psychometric Properties Using Rasch Measurement

Asian Social Science ◽

10.5539/ass.v12n8p212 ◽

2016 ◽

Vol 12 (8) ◽

pp. 212

Author(s):

Muhammad Iqbal Tariq Idris ◽

Abdul Hafidz Omar ◽

Dayang Hjh Tiawa Awang Hj Hamid ◽

Fahmi Bahri Sulaiman

Keyword(s):

Physical Activity ◽

Psychometric Properties ◽

Healthy Eating ◽

Rasch Model ◽

Rasch Measurement ◽

Mental Toughness ◽

Validity And Reliability ◽

Item Fit ◽

The Rasch Model ◽

Physical Care

<p>Hajj Instrument (HAJI) was developed to determine hajj pilgrim’s wellness. This study used Rasch measurement to evaluate the psychometric properties including validity and reliability of the HAJI. The respondents involved in this study were 300 comprised of Malaysian hajj pilgrims. HAJI consists of eight constructs namely physical care, physical activity, healthy eating, knowledge, mental toughness, intrapersonal, interpersonal and relationship with Creator and natures. Validity of each construct and content was determined through dimensionality, item fit and item polarity while the reliability was achieved by administered person and item separation. The results showed that the reliability for both item and person were 0.99 and 0.96 respectively. Besides, there were no items need to be dropped based on PTMEA CORR and INFIT MNSQ results. The study revealed that the items of HAJI fit the Rasch model as well as able to measure hajj pilgrim’s wellness. </p>

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Comparing item parameter estimates and fit statistics of the Rasch model from three different traditions

Jurnal Penelitian dan Evaluasi Pendidikan ◽

10.21831/pep.v24i1.29871 ◽

2020 ◽

Vol 24 (1) ◽

Author(s):

Bahrul Hayat ◽

Muhammad Dwirifqi Kharisma Putra ◽

Bambang Suryadi

Keyword(s):

Factor Analysis ◽

Rasch Model ◽

Measurement Model ◽

Rasch Measurement ◽

Item Parameter ◽

Rasch Models ◽

Rasch Measurement Model ◽

Item Factor Analysis ◽

The Rasch Model ◽

Special Case

Rasch model is a method that has a long history in its application in the fields of social and behavioral sciences including educational measurement. Under certain circumstances, Rasch models are known as a special case of Item response theory (IRT), while IRT is equivalent to the Item Factor Analysis (IFA) models as a special case of Structural Equation Models (SEM), although there are other ‘tradition’ that consider Rasch measurement models not part of both. In this study, a simulation study was conducted to using simulated data to explain how the interrelationships between the Rasch model as a constraint version of 2-parameter logistic (2-PL) IRT, Rasch model as an item factor analysis were compared with the Rasch measurement model using Mplus, IRTPRO and WINSTEPS program, each of which came from its own 'tradition'. The results of this study indicate that Rasch models and IFA as a special case of SEM are mathematically equal, as well as the Rasch measurement model, but due to different philosophical perspectives people might vary in their understanding about this concept. Given the findings of this study, it is expected that confusion and misunderstanding between the three can be overcome.

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Ready for school? Ready for learning? An empirical contribution to a perennial debate

The Australian Educational and Developmental Psychologist ◽

10.1017/s0816512200028303 ◽

2001 ◽

Vol 18 (1) ◽

pp. 77-80 ◽

Cited By ~ 2

Author(s):

Trevor G. Bond

Keyword(s):

Rasch Model ◽

Developmental Psychology ◽

Analytical Techniques ◽

Rasch Measurement ◽

Research Data ◽

Model Sets ◽

Unit Value ◽

Australian Council ◽

The Rasch Model ◽

Better Than

The Rasch measurement principles espoused in the Bond & Fox (2001) volume reviewed elsewhere in this journal are routinely adopted by Australia's major educational measurement projects (e.g., by Australian Council for Educational Research, Educational Testing Centre). Yet those ideas are yet to have their full impact in smaller research projects in educational and developmental psychology. A number of quantitative analytical techniques used in our disciplines are able to help us to draw conclusions like “Betty is better than or more developed than Bob”, but Rasch measurement is uniquely placed to help us conclude that “Betty is this much better than or more developed than Bob.” In educational and psychological statistics, we regularly presume the “interval” nature of our research data, but only the Rasch model sets about to ensure that the units of measurement maintain their unit value across the whole achievement or development scale.

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Le Modele De Rasch

Toegepaste Taalwetenschap in Artikelen ◽

10.1075/ttwia.31.07jon ◽

1988 ◽

Vol 31 ◽

pp. 57-70

Author(s):

John H.A.L. de Jong

Keyword(s):

Rasch Model ◽

Reliability And Validity ◽

Test Reliability ◽

Stochastic Independence ◽

Validation Procedure ◽

Local Stochastic Independence ◽

The One ◽

Definition Of ◽

Latent Traits ◽

The Rasch Model

This paper provides an elementary introduction to the one parameter psychometric model known as the Rasch model. It explains the basic principles underlying the model and the concepts of unidimensionality, local stochastic independence, and additivity in non-mathematical terms. The requirements of measurement procedures, the measurement of latent traits, the control on model fit, and the definition of a trait are discussed. It is argued that the Rasch model is particularly appropriate to understand the mutual dependence of test reliability and validity. Examples from foreign language listening comprehension tests are used to illustrate the application of the model to a test validation procedure.

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The Extended Barthel Index (EBI) can Be Reported as a Unidimensional Interval-Scaled Metric – A Psychometric Study

Physikalische Medizin Rehabilitationsmedizin Kurortmedizin ◽

10.1055/a-0820-4642 ◽

2019 ◽

Vol 29 (04) ◽

pp. 224-232 ◽

Cited By ~ 3

Author(s):

Roxanne Maritz ◽

Alan Tennant ◽

Carolina Saskia Fellinghauer ◽

Gerold Stucki ◽

Birgit Prodinger ◽

...

Keyword(s):

Rasch Model ◽

Barthel Index ◽

Rasch Analysis ◽

Scale Transformation ◽

Interval Scale ◽

Psychometric Study ◽

Calibration Sample ◽

Sum Score ◽

The Rasch Model ◽

Musculoskeletal Rehabilitation

Abstract Background The Extended Barthel Index (EBI), consisting of the original Barthel Index plus 6 cognitive items, provides a tool to monitor patients’ outcomes in rehabilitation. Whether the EBI provides a unidimensional metric, thus can be reported as a valid sum-score, remains to be examined. Objective To examine whether the EBI can be reported as unidimensional interval-scaled metric for neurological and musculoskeletal rehabilitation. Methods Rasch analysis of a calibration sample of 800 cases from neurological or musculoskeletal rehabilitation in 2016 in Switzerland. Results In the baseline analysis no fit to the Rasch Model was achieved. When accommodating local dependencies with a testlet approach satisfactory fit to the Rasch Model was achieved, and an interval scale transformation table was created. Conclusion The results support the reporting of adapted EBI total scores for both rehabilitation groups by applying the interval scaled transformation table presented in this study.

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A Rasch Analysis of the Tims, Bakker, and Derks (2012) Job Crafting Scale

Journal of Career Assessment ◽

10.1177/1069072718788787 ◽

2018 ◽

Vol 27 (4) ◽

pp. 579-593

Author(s):

Sergio L. Peral ◽

Madelyn Geldenhuys

Keyword(s):

South African ◽

Rasch Model ◽

Rasch Analysis ◽

Well Being ◽

Job Crafting ◽

Research Attention ◽

Men And Women ◽

Item Functioning ◽

Validation Technique ◽

The Rasch Model

A Rasch validation was performed on the Tims, Bakker, and Derks’s Job Crafting Scale (JCS) in the South African working context. The JCS, which has been linked to employee well-being and career-related outcomes, continues to be the most widely used measure of job crafting behavior. Data obtained from the JCS generally showed good fit to the Rasch model. Four items were flagged during the analysis for displaying misfit (1 item) or differential item functioning (3 items), warranting further research attention. The study disclosed the dimensionality of the JCS, the hierarchical ordering and fit of the items, the functionality of the response format, and the ability of the JCS to measure invariantly across men and women, yielding new and interesting insights into the psychometric properties of the scale. The study contributes to research concerning the validity of the JCS in a non-European context, particularly through the use of Rasch analysis as a validation technique.

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Investigating Psychometric Properties of the Arm Activity Measure – Thai Version (ArmA-TH) Sub-Scales Using the Rasch Model

10.21203/rs.3.rs-117526/v1 ◽

2020 ◽

Author(s):

Montana Buntragulpoontawee ◽

Jeeranan Khunachiva ◽

Patreeya Euawongyarti ◽

Nahathai Wongpakaran ◽

Tinakon Wongpakaran ◽

...

Keyword(s):

Rasch Model ◽

Rasch Analysis ◽

Measurement Properties ◽

Brain Disorders ◽

Local Independence ◽

Fit Statistics ◽

Active Function ◽

Item Functioning ◽

The Rasch Model ◽

Activity Measure

Abstract Background: This study investigated the ArmA-TH measurement properties based on item response theory, using the Rasch model. Methods: Patients with upper limb hemiplegia resulting from cerebrovascular and other brain disorders were asked to completed the ArmA-TH questionnaire. Rasch analysis was performed to test how well the ArmA-TH passive and active function sub-scales fit the Rasch model by investigating unidimensionality, response category functioning, reliability of the person and item, and differential item functioning (DIF) for age, sex and education. Results: Participants had stroke or other acquired brain injury (n=185) and the majority were men 126(68.1%), with a mean age of 55(SD 22). Most patients 91(49.2%) graduated elementary/primary school. For the ArmA-TH passive function scale, all items had acceptable fit statistics. The scale’s unidimensionality, and local independence were supported. The reliability was acceptable. Disordered threshold was found in five items, none was DIF. For the ArmA-TH active function scale, one item was misfitting and three were locally dependent. The reliability was good. DIF was not found. All items had disordered thresholds, and data fitted the Rasch model better after rescoring.Conclusions: Both sub-scales of ArmA-TH fitted the Rasch model, and are valid and reliable. The disordered thresholds should be further investigated.

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Rasch analysis of the living with chronic illness scale in Parkinson’s disease

BMC Neurology ◽

10.1186/s12883-020-01926-7 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Leire Ambrosio ◽

Carmen Rodriguez-Blazquez ◽

Alba Ayala ◽

Maria João Forjaz

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Chronic Illness ◽

Latin American ◽

Rasch Model ◽

Rasch Analysis ◽

Response Scale ◽

Clinical Tool ◽

Cross Sectional ◽

The Rasch Model

Abstract Background Neurologists play an essential role in facilitating the patient’s process of living with Parkinson’s disease (PD). The Living with Chronic Illness Scale-PD (LW-CI-PD) is a unique available clinical tool that evaluates how the patient is living with PD. The objective of the study was to analyse the LW-CI-PD properties according to the Rasch model. Methods An open, international, cross-sectional study was carried out in 324 patients with Parkinson’s disease from four Latin American countries and Spain. Psychometric properties of the LW-CI-PD were tested using Rasch analysis: fit to the Rasch model, item local independency, unidimensionality, reliability, and differential item functioning by age and gender. Results Original LW-CI-PD do not fit Rasch model. Modifications emerged included simplifying the response scale and deleting misfit items, the dimensions Acceptance, Coping and Integration showed a satisfactory fit to the Rasch model, with reliability indices greater than 0.70. The dimensions Self-management and Adjustment to the disease did not reach fit to the Rasch model. Conclusion Suggestions for improving the LW-CI-PD include a multidimensional and shorter scale with 12 items grouped in three subscales with a simpler response scheme. The final LW-CI-PD Scale version is a reliable scale, with good internal construct validity, that provides Rasch transformed results on linear metric scale.

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