MCMC Z-G: An IRT Computer Program for Forced-Choice Noncognitive Measurement

Document Type

Article

Publication Date

2016

Keywords

item response theory, Zinnes–Griggs or Z-G model, forced-choice, noncognitive measurement, MCMC

Digital Object Identifier (DOI)

https://doi.org/10.1177/0146621616663682

Abstract

In recent years, there has been a surge of interest in measuring noncognitive constructs in educational and managerial/organizational settings. For the most part, these noncognitive constructs have been and continue to be measured using Likert-type (ordinal response) scales, which are susceptible to several types of response distortion. To deal with these response biases, researchers have proposed using forced-choice format, which requires respondents or raters to evaluate cognitive, affective, or behavioral descriptors presented in blocks of two or more. The workhorse for this measurement endeavor is the item response theory (IRT) model developed by Zinnes and Griggs (Z-G), which was first used as the basis for a computerized adaptive rating scale (CARS), and then extended by many organizational scientists. However, applications of the Z-G model outside of organizational contexts have been limited, primarily due to the lack of publicly available software for parameter estimation. This research effort addressed that need by developing a Markov chain Monte Carlo (MCMC) estimation program, called MCMC Z-G, which uses a Metropolis-Hastings-within-Gibbs algorithm to simultaneously estimate Z-G item and person parameters. This publicly available computer program MCMC Z-G can run on both Mac OS® and Windows® platforms.

Was this content written or created while at USF?

Yes

Citation / Publisher Attribution

Applied Psychological Measurement, v. 40, issue 7, p. 551-553

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