The current study aimed to determine the best method for estimating latent variable interactions as a function of the size of the interaction effect, sample size, the loadings of the indicators, the size of the relation between the first-order latent variables, and normality. Data were simulated...

Measuring continuous change or growth in individual students' academic abilities over time currently uses several statistical models or transformations to move from data representing a student's correct or incorrect responses on individual test items to inferences about the form and quantity of...

As researchers begin to use Growth Mixture Models (GMM) with data from nationally representative samples, it becomes increasingly critical for researchers to understand the difficulties associated with modeling data that come from complex sample designs. If researchers naively apply GMM to...

Growth mixture modeling has gained much attention in applied and methodological social science research recently, but the selection of the number of latent classes for such models remains a challenging issue. This problem becomes more serious when one of the key assumptions of this model, proper...