Model Specification Issues With the Latent Variable Interaction Model

• In Event: Advanced Topics in Structural Equation Modeling

Abstract

Several studies have stressed the importance of simultaneously estimating interaction and quadratic effects in multiple regression analyses, even if theory only suggests an interaction effect should be present (Cortina, 1993; Ganzach, 1997; Lubinski & Humphreys, 1990). Specifically, these studies found that failing to simultaneously include quadratic effects when testing for interaction effects could result in Type I errors, Type II errors, or misleading interactions. Research investigating this issue have been limited to multiple regression models. Contrarily, structural equation modeling (SEM) is a more appropriate analysis when hypotheses include latent variables. The current study utilized monte carlo simulation to investigate whether quadratic effects should be included in the latent variable interaction model. Recommendations for applied researchers will be provided.

Authors

• Brandi A. Weiss, The George Washington University

• Jaehwa Choi, The George Washington University