Table 6.

Comparison of Regression Interactions and Regression Mixture Models.

Regression interactions	Regression mixtures
Research questions
Tests hypotheses about heterogeneity in an effect because of an a priori identified predictor	Explores for any evidence of discrete heterogeneity in effects
Types of heterogeneity identified
DTiscrete or continuous heterogeneity that is a linear funciton of a predictor	Discrete heterogeneity in effects
Model assumptions
Normal residuals—Affects standard errors	Normal residuals—Affects parameter estimates
Errors and independent and constant across all predictors	Errors and independent and constant across x variables
Relationships are linear	Relationships are linear
All predictors are measured without error	x Variables are measured without error
	z Variables need to be measured without error for the relationship between z and latent classes to be unbiased
Sample size required
Moderate samples required	Large samples required