Digital Module 03: Nonparametric Item Response Theory

5 (5 votes)

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: nonparametric IRT; Mokken scaling; monotone homogeneity model; double monotonicity model; rater effects; multilevel modeling; mokken package; R

Key:

Complete
Failed
Available
Locked
Digital Module (COMPLETE INTERACTIVE VERSION)
Recorded 03/16/2019
Recorded 03/16/2019 Full digital module with all resources and activities.
DM03 VIDEO (Sections 1-4)
Open to view video.
Open to view video. A video version of sections 1-4 without interactive components but with all core content.
Worked Examples VIDEO (Part 1, R Installation)
Open to view video.
Open to view video. This video provides instruction on how to install the mokken package from R and how to prepare the data for analysis [approximately 8 minutes].
Worked Examples VIDEO (Part 2, Dichotomous Data)
Open to view video.
Open to view video. This video provides an overview of model estimation and parameter interpretation for dichotomous data [approximately 12 minutes].
Worked Examples VIDEO (Part 3, Polytomous Data)
Open to view video.
Open to view video. This video provides an overview of model estimation and parameter interpretation for polytomous data [approximately 17 minutes].

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@au.edu