Module 41:Latent DIF Analysis using Mixture Item Response Models

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The purpose of this ITEMS module is to provide an introduction to differential item functioning (DIF) analysis using mixture item response models. The mixture item response models for DIF analysis involve comparing item profiles across latent groups, instead of manifest groups. First, an overview of DIF analysis based on latent groups, called latent DIF analysis, is provided and its applications in the literature are surveyed. Then, the methodological issues pertaining to latent DIF analysis are described, including mixture item response models, parameter estimation, and latent DIF detection methods. Finally, recommended steps for latent DIF analysis are illustrated using empirical data.

Keywords: differential item functioning, DIF, estimation, latent class, latent DIF,  item response model, IRT, mixture model, model fit, model selection

Sun-Joo Cho

Associate Professor, Department of Psychology and Human Development, Vanderbilt University, Nashville, TN

Dr. Cho has collaborated with researchers from a variety of disciplines including reading education, math education, special education, psycholinguistics, clinical psychology, cognitive psychology, neuropsychology, and audiology. She serves on the editorial boards of Journal of Educational PsychologyBehavior Research Methods, and International Journal of Testing

Youngsuk Suh

Department of Educational Psychology, Rutgers, The State University of New Jersey, New Brunswick, NJ

Woo-yeol Lee

Graduate Student, Department of Psychology and Human Development, Vanderbilt University, Nashville, TN


Module 41: An NCME Instructional Module on Latent DIF Analysis Using Mixture Item Response Models
Open to download resource.
Open to download resource.