Title

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

Document Type

Article

Language

eng

Publication Date

10-1-2017

Publisher

SAGE Publishing

Source Publication

Journal of Educational and Behavioral Statistics

Source ISSN

1076-9986

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.

Comments

Journal of Educational and Behavioral Statistics, Vol. 42, No. 5 (October 1, 2017): 531-558. DOI.

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