Publication:
Primary Principles in Developing Scale With Rasch Analysis: Portfolio Anxiety Assessment

dc.authorscopusid8639397400
dc.authorscopusid35484908800
dc.contributor.authorTomak, L.
dc.contributor.authorMidik, O.
dc.date.accessioned2020-06-21T13:06:50Z
dc.date.available2020-06-21T13:06:50Z
dc.date.issued2018
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Tomak] Leman, Department of Biostatistics and Medical Informatics, Ondokuz Mayis Üniversitesi, Samsun, Turkey; [Midik] Özlem, Department of Medical Education, Ondokuz Mayis Üniversitesi, Samsun, Turkeyen_US
dc.description.abstractBackground: Rasch model is a useful method for developing a new scale. This study aims to determine the fitting between data obtained from answers for a portfolio anxiety scale and Rasch model and describes how the scale can be modified to increase the fitting through different steps. Materials and Methods: A portfolio scale was applied to 171 students of the Faculty of Medicine, Ondokuz Mayis University. The partial credit model was used, and fit statistics were assessed to determine the fitting of the data to Rasch model. Person separation index (PSI) was used for reliability. Results: For a satisfaction subscale, the average item fit residual value was 0.47 and the average person fit residual value was -0.29. For the item-trait χ2 interaction, P = 0.655 and PSI = 0.81. For a writing anxiety subscale, the average item fit residual value was 0.08 and the average person fit residual value was -0.24. For the item-trait χ2 interaction, P = 0.698 and PSI = 0.73. For a reflection anxiety subscale, the average item fit residual value was 0.64 and the average item fit residual value was 0.64. For the item-trait χ2 interaction, P = 0.195 and PSI = 0.73. Conclusion: The validity and reliability of Rasch analysis portfolio scale were analyzed, and items that worked well were included in the study. The results show that Rasch model provides a more accurate analysis for developing and adapting scales. Both the fit statistics and fit graphs help improve the analyses. © 2018 Nigerian Journal of Clinical Practice | Published by Wolters Kluwer - Medknow.en_US
dc.identifier.doi10.4103/njcp.njcp_275_17
dc.identifier.endpage1303en_US
dc.identifier.issn1119-3077
dc.identifier.issue10en_US
dc.identifier.pmid30297562
dc.identifier.scopus2-s2.0-85054780655
dc.identifier.scopusqualityQ2
dc.identifier.startpage1296en_US
dc.identifier.urihttps://doi.org/10.4103/njcp.njcp_275_17
dc.identifier.urihttps://hdl.handle.net/20.500.12712/11419
dc.identifier.volume21en_US
dc.identifier.wosWOS:000446795500010
dc.identifier.wosqualityQ3
dc.language.isoenen_US
dc.publisherWolters Kluwer Medknow Publications B9, Kanara Business Centre, off Link Road, Ghatkopar (E) Mumbai 400 075en_US
dc.relation.ispartofNigerian Journal of Clinical Practiceen_US
dc.relation.journalNigerian Journal of Clinical Practiceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectPartial Credit Modelen_US
dc.subjectPortfolioen_US
dc.subjectRasch Modelen_US
dc.subjectScale Developmenten_US
dc.titlePrimary Principles in Developing Scale With Rasch Analysis: Portfolio Anxiety Assessmenten_US
dc.typeArticleen_US
dspace.entity.typePublication

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