TCRM: Advances in Moderation Analyses: An Introduction to Mixture Regression
Leader: Justin Dyer, Ph.D., is Assistant Professor in Family Studies at Brigham Young University. He received his Ph.D. in Human Development and Family Studies from the University of Illinois at Urbana-Champaign.
TCRM: Advances in Moderation Analyses: An Introduction to Mixture Regression
Moderation analyses are typically conducted using either interaction terms or multiple group analyses. In this way, it can be examined whether the relationship between variables differs across the levels of another variable. However, it may be that the relationships amongst variables differ for certain “unobserved” or “latent” subgroups within a population (i.e., groups that are not directly observed). Mixture regression (a type of finite mixture model/latent class analysis) is a method to examine whether the relationships between independent and dependent variables differ for latent classes. That is, mixture regression identifies classes for whom the relationships between the independent and dependent variables differ. This method to examine moderation is highly flexible, identifying a multiple of groups for whom variables are differentially related and allows for examining the characteristics of those groups.