ITEMS Portal
Digital Module 03: Nonparametric Item Response Theory
Recorded On: 09/24/2019
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In this digital ITEMS module Stefanie Wind introduces the framework of nonparametric item response theory (IRT), in particular Mokken scaling, which can be used to evaluate fundamental measurement properties with less strict assumptions than parametric IRT models. She walks through the key distinction between parametric and nonparametric models, introduces the two key nonparametric models under Mokken scaling – the monotone homogeneity and double monotonicity model – and discusses modern extensions of the basic models. She also describes how researchers and practitioners can use key nonparametric statistics and graphical visualization tools to evaluate the fundamental measurement properties of an assessment from a nonparametric perspective. Finally, Dr. Wind illustrates the key reasoning steps and associated best practices using video-based worked examples completed with the mokken package in R.
Keywords: double monotonicity model, DMM, item response theory, IRT, Mokken scaling, monotone homogeneity model, multilevel modeling, mokken package, nonparametric IRT, R, rater effects
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Stefanie A. Wind
Assistant Professor, Department of Educational Research, University of Alabama, Tuscaloosa, AL
Dr. Wind conducts methodological and applied research on educational assessments with an emphasis on issues related to raters, rating scales, Rasch models, nonparametric IRT, and parametric IRT.
Contact Stefanie via stefanie.wind@ua.edu
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