Latent Variable Interaction Modeling

Abstract

Abstract Latent variable interaction modeling with continuous observed variables is presented using 2 different approaches. The 1st approach analyzes data using a LISREL 8.30 program where the latent interaction variable is defined by multiplying pairs of observed variables. The 2nd approach analyzes data using PRELIS2 and SIMPLIS programs where the latent interaction variable is defined by multiplying the latent variable scores of the exogeneous latent independent variables. The programs used to create the multivariate normal observed variables and conduct the analyses for the 2 different approaches are given in the appendixes. The product indicant and latent variable score approach produced similar gamma coefficients in their hypothesized models but differed in their standard errors for the gamma coefficients. The latent variable score approach holds the promise of being easier to implement and can be applied to more complex latent variable interaction models.