Semi-automated Rasch analysis with differential item functioning.

Autor: Wijayanto F; Institute for Computing and Information Sciences, Radboud University Nijmegen, Nijmegen, The Netherlands. f.wijayanto@cs.ru.nl.; Department of Informatics, Universitas Islam Indonesia, Yogyakarta, Indonesia. f.wijayanto@cs.ru.nl., Bucur IG; Institute for Computing and Information Sciences, Radboud University Nijmegen, Nijmegen, The Netherlands., Mul K; Department of Neurology, Donders Institute for Brain, Cognition, and Behaviour, Nijmegen, The Netherlands., Groot P; Institute for Computing and Information Sciences, Radboud University Nijmegen, Nijmegen, The Netherlands., van Engelen BGM; Department of Neurology, Donders Institute for Brain, Cognition, and Behaviour, Nijmegen, The Netherlands., Heskes T; Institute for Computing and Information Sciences, Radboud University Nijmegen, Nijmegen, The Netherlands.
Jazyk: angličtina
Zdroj: Behavior research methods [Behav Res Methods] 2023 Sep; Vol. 55 (6), pp. 3129-3148. Date of Electronic Publication: 2022 Sep 07.
DOI: 10.3758/s13428-022-01947-9
Abstrakt: Rasch analysis is a procedure to develop and validate instruments that aim to measure a person's traits. However, manual Rasch analysis is a complex and time-consuming task, even more so when the possibility of differential item functioning (DIF) is taken into consideration. Furthermore, manual Rasch analysis by construction relies on a modeler's subjective choices. As an alternative approach, we introduce a semi-automated procedure that is based on the optimization of a new criterion, called in-plus-out-of-questionnaire log likelihood with differential item functioning (IPOQ-LL-DIF), which extends our previous criterion. We illustrate our procedure on artificially generated data as well as on several real-world datasets containing potential DIF items. On these real-world datasets, our procedure found instruments with similar clinimetric properties as those suggested by experts through manual analyses.
(© 2022. The Author(s).)
Databáze: MEDLINE
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