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Autori principali: Kaptur, Dandan Chen, Zhang, Jinming
Natura: Preprint
Pubblicazione: 2024
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Accesso online:https://arxiv.org/abs/2408.11922
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author Kaptur, Dandan Chen
Zhang, Jinming
author_facet Kaptur, Dandan Chen
Zhang, Jinming
contents This study evaluated four multi-group differential item functioning (DIF) methods (the root mean square deviation approach, Wald-1, generalized logistic regression procedure, and generalized Mantel-Haenszel method) via Monte Carlo simulation of controlled testing conditions. These conditions varied in the number of groups, the ability and sample size of the DIF-contaminated group, the parameter associated with DIF, and the proportion of DIF items. When comparing Type-I error rates and powers of the methods, we showed that the RMSD approach yielded the best Type-I error rates when it was used with model-predicted cutoff values. Also, this approach was found to be overly conservative when used with the commonly used cutoff value of 0.1. Implications for future research for educational researchers and practitioners were discussed.
format Preprint
id arxiv_https___arxiv_org_abs_2408_11922
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Evaluating Four Methods for Detecting Differential Item Functioning in Large-Scale Assessments with More Than Two Groups
Kaptur, Dandan Chen
Zhang, Jinming
Applications
This study evaluated four multi-group differential item functioning (DIF) methods (the root mean square deviation approach, Wald-1, generalized logistic regression procedure, and generalized Mantel-Haenszel method) via Monte Carlo simulation of controlled testing conditions. These conditions varied in the number of groups, the ability and sample size of the DIF-contaminated group, the parameter associated with DIF, and the proportion of DIF items. When comparing Type-I error rates and powers of the methods, we showed that the RMSD approach yielded the best Type-I error rates when it was used with model-predicted cutoff values. Also, this approach was found to be overly conservative when used with the commonly used cutoff value of 0.1. Implications for future research for educational researchers and practitioners were discussed.
title Evaluating Four Methods for Detecting Differential Item Functioning in Large-Scale Assessments with More Than Two Groups
topic Applications
url https://arxiv.org/abs/2408.11922