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Interpreting results from Rasch analysis 2. Advanced model applications and the data-model fit assessment.

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Title: Interpreting results from Rasch analysis 2. Advanced model applications and the data-model fit assessment.
Authors: Tesio, Luigi (AUTHOR), Caronni, Antonio (AUTHOR), Simone, Anna (AUTHOR), Kumbhare, Dinesh (AUTHOR), Scarano, Stefano (AUTHOR)
Source: Disability & Rehabilitation. Feb2024, Vol. 46 Issue 3, p604-617. 14p.
Subjects: Physical diagnosis, Statistics, Computer simulation, Experimental design, Research evaluation, Mathematical models, Activities of daily living, Psychometrics, Questionnaires, Theory, Data analysis, Statistical models
Abstract: Purpose: The present paper presents developments and advanced practical applications of Rasch's theory and statistical analysis to construct questionnaires for measuring a person's traits. The flaws of questionnaires providing raw scores are well known. Scores only approximate objective, linear measures. The Rasch Analysis allows you to turn raw scores into measures with an error estimate, satisfying fundamental measurement axioms (e.g., unidimensionality, linearity, generalizability). A previous companion article illustrated the most frequent graphic and numeric representations of results obtained through Rasch Analysis. A more advanced description of the method is presented here. Conclusions: Measures obtained through Rasch Analysis may foster the advancement of the scientific assessment of behaviours, perceptions, skills, attitudes, and knowledge so frequently faced in Physical and Rehabilitation Medicine, not less than in social and educational sciences. Furthermore, suggestions are given on interpreting and managing the inevitable discrepancies between observed scores and ideal measures (data-model "misfit"). Finally, twelve practical take-home messages for appraising published results are provided. The current work is the second of two papers addressed to rehabilitation clinicians looking for an in-depth introduction to the Rasch analysis. The first paper illustrates the most common results reported in published papers presenting the Rasch analysis of questionnaires. The present article illustrates more advanced applications of the Rasch analysis, also frequently found in publications. Twelve take-home messages are given for a critical appraisal of the results. [ABSTRACT FROM AUTHOR]
Copyright of Disability & Rehabilitation is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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DbLabel: Psychology and Behavioral Sciences Collection
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Interpreting results from Rasch analysis 2. Advanced model applications and the data-model fit assessment.
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  Data: <searchLink fieldCode="AR" term="%22Tesio%2C+Luigi%22">Tesio, Luigi</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Caronni%2C+Antonio%22">Caronni, Antonio</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Simone%2C+Anna%22">Simone, Anna</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kumbhare%2C+Dinesh%22">Kumbhare, Dinesh</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Scarano%2C+Stefano%22">Scarano, Stefano</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Disability+%26+Rehabilitation%22">Disability & Rehabilitation</searchLink>. Feb2024, Vol. 46 Issue 3, p604-617. 14p.
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  Data: <searchLink fieldCode="DE" term="%22Physical+diagnosis%22">Physical diagnosis</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+simulation%22">Computer simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Experimental+design%22">Experimental design</searchLink><br /><searchLink fieldCode="DE" term="%22Research+evaluation%22">Research evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink><br /><searchLink fieldCode="DE" term="%22Activities+of+daily+living%22">Activities of daily living</searchLink><br /><searchLink fieldCode="DE" term="%22Psychometrics%22">Psychometrics</searchLink><br /><searchLink fieldCode="DE" term="%22Questionnaires%22">Questionnaires</searchLink><br /><searchLink fieldCode="DE" term="%22Theory%22">Theory</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+models%22">Statistical models</searchLink>
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  Data: Purpose: The present paper presents developments and advanced practical applications of Rasch's theory and statistical analysis to construct questionnaires for measuring a person's traits. The flaws of questionnaires providing raw scores are well known. Scores only approximate objective, linear measures. The Rasch Analysis allows you to turn raw scores into measures with an error estimate, satisfying fundamental measurement axioms (e.g., unidimensionality, linearity, generalizability). A previous companion article illustrated the most frequent graphic and numeric representations of results obtained through Rasch Analysis. A more advanced description of the method is presented here. Conclusions: Measures obtained through Rasch Analysis may foster the advancement of the scientific assessment of behaviours, perceptions, skills, attitudes, and knowledge so frequently faced in Physical and Rehabilitation Medicine, not less than in social and educational sciences. Furthermore, suggestions are given on interpreting and managing the inevitable discrepancies between observed scores and ideal measures (data-model "misfit"). Finally, twelve practical take-home messages for appraising published results are provided. The current work is the second of two papers addressed to rehabilitation clinicians looking for an in-depth introduction to the Rasch analysis. The first paper illustrates the most common results reported in published papers presenting the Rasch analysis of questionnaires. The present article illustrates more advanced applications of the Rasch analysis, also frequently found in publications. Twelve take-home messages are given for a critical appraisal of the results. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Disability & Rehabilitation is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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        Value: 10.1080/09638288.2023.2169772
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      – Code: eng
        Text: English
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        PageCount: 14
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      – SubjectFull: Physical diagnosis
        Type: general
      – SubjectFull: Statistics
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      – SubjectFull: Computer simulation
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      – SubjectFull: Experimental design
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      – SubjectFull: Research evaluation
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      – SubjectFull: Mathematical models
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      – SubjectFull: Psychometrics
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      – SubjectFull: Questionnaires
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      – SubjectFull: Theory
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      – SubjectFull: Data analysis
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      – SubjectFull: Statistical models
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      – TitleFull: Interpreting results from Rasch analysis 2. Advanced model applications and the data-model fit assessment.
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              M: 02
              Text: Feb2024
              Type: published
              Y: 2024
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