Item Response Modeling of Multivariate Count Data With Zero Inflation, Maximum Inflation, and Heaping

Brooke E. Magnus and David Thissen
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Brooke E. Magnus: Marquette University
David Thissen: University of North Carolina

Journal of Educational and Behavioral Statistics, 2017, vol. 42, issue 5, 531-558

Abstract: Questionnaires that include items eliciting count responses are becoming increasingly common in psychology. This study proposes methodological techniques to overcome some of the challenges associated with analyzing multivariate item response data that exhibit zero inflation, maximum inflation, and heaping at preferred digits. The modeling framework combines approaches from three literatures: item response theory (IRT) models for multivariate count data, latent variable models for heaping and extreme responding, and mixture IRT models. Data from the Behavioral Risk Factor Surveillance System are used as a motivating example. Practical implications are discussed, and recommendations are provided for researchers who may wish to use count items on questionnaires.

Keywords: count data; zero inflation; heaping; item response theory (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:42:y:2017:i:5:p:531-558

DOI: 10.3102/1076998617694878

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