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Multidimensional Extension of Multiple Indicators Multiple Causes Models to Detect DIF

Bibliographic Data

ID20471985
AuthorsSoo In Lee (0000-0003-4023-8841, American Institutes for Research), Soo Lee (American Institutes for Research, Washington, DC, USA), Okan Bulut (0000-0001-5853-1267, University of Alberta, Edmonton, Alberta, Canada, corresponding author), Youngsuk Suh (0000-0001-7197-6383, Rutgers, The State University of New Jersey, New Brunswick, NJ, USA)
Year2016
Volume77
Issue4
Pages545-569
Publication date2016-05-25
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEducational and Psychological Measurement (JOURNAL)
Journal identifiersISSN: 0013-1644 • E-ISSN: 1552-3888
PublisherSAGE Publishing (PUBLISHER • US)
DOI10.1177/0013164416651116
PMID30034019
OpenAlexW2406198090
LanguageEN
Citations received5
References cited30

A number of studies have found multiple indicators multiple causes (MIMIC) models to be an effective tool in detecting uniform differential item functioning (DIF) for individual items and item bundles. A recently developed MIMIC-interaction model is capable of detecting both uniform and nonuniform DIF in the unidimensional item response theory (IRT) framework. The goal of the current study is to extend the MIMIC-interaction model for detecting DIF in the context of multidimensional IRT modelling and examine the performance of the multidimensional MIMIC-interaction model under various simulation conditions with respect to Type I error and power rates. Simulation conditions include DIF pattern and magnitude, test length, correlation between latent traits, sample size, and latent mean differences between focal and reference groups. The results of this study indicate that power rates of the multidimensional MIMIC-interaction model under uniform DIF conditions were higher than those of nonuniform DIF conditions. When anchor item length and sample size increased, power for detecting DIF increased. Also, the equal latent mean condition tended to produce higher power rates than the different mean condition. Although the multidimensional MIMIC-interaction model was found to be a reasonably useful tool for identifying uniform DIF, the performance of the model in detecting nonuniform DIF appeared to be questionable

Context (archaeology) · Correlation · Differential item functioning · Econometrics · Item response theory · Psychometrics · Sample size determination · Statistical power · Statistics · Type I and type II errors · Advanced Statistical Modeling Techniques · Cognitive Abilities and Testing · Mathematics · Psychometric Methodologies and Testing

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Unique citing works5
Citations per year0,63
Citation span2018 - 2024 (7)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 5

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