Bayesian estimation of single and multilevel models with latent variable interactions

2020 ◽  
pp. 1-15
Author(s):  
Tihomir Asparouhov ◽  
Bengt Muthén
Keyword(s):  
Bayesian Estimation ◽  
Latent Variable ◽  
Multilevel Models ◽  
Latent Variable Interactions ◽  
Variable Interactions

scholarly journals Latent Variable Interactions With Ordered-Categorical Indicators: Comparisons of Unconstrained Product Indicator and Latent Moderated Structural Equations Approaches

2019 ◽  
Vol 80 (2) ◽  
pp. 262-292 ◽  
Author(s):  
Ezgi Aytürk ◽  
Heining Cham ◽  
Patricia A. Jennings ◽  
Joshua L. Brown
Keyword(s):  
Latent Variable ◽  
English Language ◽  
Structural Equations ◽  
Fifth Grade Students ◽  
Teacher Student ◽  
Interaction Modeling ◽  
Latent Variable Interactions ◽  
Ordered Categorical ◽  
Latent Moderated Structural Equations ◽  
Variable Interactions

Methods to handle ordered-categorical indicators in latent variable interactions have been developed, yet they have not been widely applied. This article compares the performance of two popular latent variable interaction modeling approaches in handling ordered-categorical indicators: unconstrained product indicator (UPI) and latent moderated structural equations (LMS). We conducted a simulation study across sample sizes, indicators’ distributions and category conditions. We also studied four strategies to create sets of product indicators for UPI. Results supported using a parceling strategy to create product indicators in the UPI approach or using the LMS approach when the categorical indicators are symmetrically distributed. We applied these models to study the interaction effect between third- to fifth-grade students’ social skills improvement and teacher–student closeness on their state English language arts test scores.

Integrating Moderation and Mediation

2016 ◽  
Vol 20 (4) ◽  
pp. 721-745 ◽  
Author(s):  
Shruti R. Sardeshmukh ◽  
Robert J. Vandenberg
Keyword(s):  
Structural Equation Modeling ◽  
Research Methods ◽  
Latent Variable ◽  
Structural Equation ◽  
Equation Modeling ◽  
Latent Variable Interactions ◽  
Variable Interactions ◽  
Do So

It is increasingly common to test hypotheses combining moderation and mediation. Structural equation modeling (SEM) has been the favored approach to testing mediation hypotheses. However, the biggest challenge to testing moderation hypotheses in SEM was the complexity underlying the modeling of latent variable interactions. We discuss the latent moderated structural equation procedure (LMS) approach to specifying latent variable interactions, which is implemented in Mplus, and offer a simple and accessible way of testing combined moderation and mediation hypotheses using SEM. To do so, we provide sample code for six commonly encountered moderation and mediation cases and relevant equations that can be easily adapted to researchers’ data. By articulating the similarities in the two different approaches, discussing the combination of moderation and mediation, we also contribute to the research methods literature.

Estimating La tent Variable Interactions and Quadratics: The State of This Art

1996 ◽  
Vol 22 (1) ◽  
pp. 163-183 ◽  
Author(s):  
Robert A. Ping
Keyword(s):  
Latent Variable ◽  
Structural Equation ◽  
The State ◽  
Detection Techniques ◽  
Structural Equation Analysis ◽  
Recent Advances ◽  
Equation Analysis ◽  
Nonlinear Structural Equation ◽  
Latent Variable Interactions ◽  
Variable Interactions

Because there is little guidance for substantive researchers, the paper reviews the techniques for detecting latent variable interactions and quadratics. After examining plausible research situations where including these nonlinear variables might be appropriate, the paper describes the available detection techniques. Recent advances in nonlinear structural equation analysis are given particular attention, and suggestions for substantive researchers are made.

Sign in / Sign up

Export Citation Format

Share Document