Interactions between (multiple indicator) latent variables are rarely used because of
implementation complexity and competing strategies. Based on 4 simulation studies, the …

A Monte Carlo simulation was conducted to investigate the robustness of 4 latent variable
interaction modeling approaches (Constrained Product Indicator [CPI], Generalized …

The author proposes an alternative estimation technique for latent variable interactions and
quadratics. Available techniques for specifying these variables in structural equation models …

Little, Bovaird and Widaman (2006) proposed an unconstrained approach with residual
centering for estimating latent interaction effects as an alternative to the mean-centered …

This chapter mostly focuses on techniques to analyze interaction effects when at least one of
the predictors is a latent variable with multiple indicators. However, for didactical reasons …

Examining interactions among predictors is an important part of a developing research
program. Estimating interactions using latent variables provides additional power to detect …

Various approaches using the maximum likelihood (ML) option of the LISREL program and
products of indicators have been proposed to analyze structural equation models with non …

Standardized parameter estimates are routinely used to summarize the results of multiple
regression models of manifest variables and structural equation models of latent variables …

Structural equation modeling methods for estimating and testing hypotheses about an
interaction between continuous variables were investigated. The methods were (a) Bollen's …

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 …