Modeling Polytomous Item Responses Using Simultaneously Estimated Multinomial Logistic Regression Models

Abstract

Survey items with multiple response categories and multiple-choice test questions are ubiquitous in psychological and educational research. We illustrate the use of log-multiplicative association (LMA) models that are extensions of the well-known multinomial logistic regression model for multiple dependent outcome variables to reanalyze a set of items from a large political psychology survey. In particular, LMA models are shown to provide a useful analysis of items when the proper scoring rule for them is unclear. They also clearly reveal the performance of the items when instructions were altered to suppress “Don’t know” responses. LMA models can be fit rapidly using commonly available software.