Validation and Calibration in Mixture Modeling: The Exploratory Factor Analysis/Confirmatory Factor Analysis of Mixture Models

• In Event: Issues of Measurement Invariance in Mixture Models for Educational Data

Abstract

Mixture modeling is considered an exploratory modeling approach since, in most modeling contexts, the number and type of classes are not a priori hypothesized. As the use of mixture models becomes more common and with the availability of larger datasets and accessible open source datasets containing the same measures, a confirmatory mixture modeling approach becomes more plausible. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) are widely used in educational research to explore (EFA) and then confirm (CFA) modeling results. However, a less widely used, yet similar, approach in the context of mixture models is referred to as calibration and validation. There are many reasons this method may be underutilized, one of which we believe to be a misunderstanding of how and when to use it-- which this paper hopes to directly address.

Authors

• Delwin Carter, University of California - Santa Barbara

• Karen L. Nylund-Gibson, University of California - Santa Barbara