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

Educational and Psychological Measurement
Ezgi AytürkJoshua L Brown

Abstract

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.

References

May 31, 2007·The British Journal of Mathematical and Statistical Psychology·Dimitris Rizopoulos, Irini Moustaki
Mar 5, 2013·Multivariate Behavioral Research·Heining ChamLeona S Aiken
Jul 10, 2013·Psychological Methods·Todd D LittleAlexander M Schoemann
Apr 30, 2014·Psychological Methods·Njål Foldnes, Knut Arne Hagtvet
Apr 1, 2005·Multivariate Behavioral Research·Xin-Yuan Song, Sik-Yum Lee
Mar 26, 2016·Multivariate Behavioral Research·Njål Foldnes, Ulf Henning Olsson
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Software Mentioned

MPlus
R
ltm
R package copula
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