Moderation analyses in research typically are conducted using either interaction terms or multiple group analyses. In this way, scholars can examine whether the relationship between variables differs across the levels of another variable.

However, it may be that the relationships among 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 highly flexible method to examine whether the relationships between independent and dependent variables differ for latent classes.

By attending this webinar — presented by W. Justin Dyer, Ph.D. — you’ll receive an accessible introduction to mixture regression and be able to understand basic concepts of moderation; how mixture regression can address moderation questions that previous standard methods cannot; and how to conduct a mixture regression.

Approved for 1 CFLE contact hour of continuing education credit.

Webinar date: April 30, 2019

Fee: $25 for NCFR student members / $45 for NCFR members / $85 for nonmembers