Survey Analysis With Mixture Rasch Models

• In Event: Measurement Issues in Survey Research

Abstract

This paper seeks to provide a demonstration of the utility of mixture Rasch models (MRMs) for the analysis of survey data. Specifically, a framework based on a mixture partial credit model (MPCM) will be presented. MRMs are able to provide information regarding latent classes (subpopulations without manifest grouping variables) and separate item parameter estimates for each of these latent classes. Analyses can provide insight into how a survey scale is functioning and how survey respondents differ from one another. The paper will provide a detailed example with real survey data through all stages of model estimation and selection, description of model results, and follow-up analyses using the MRM results.

Authors

• John T. Willse, University of North Carolina at Greensboro

• Andrew Dallas, University of North Carolina - Greensboro