Exploring the Performance of Latent Moderated Structural Equations Approach for Ordered-Categorical Items. Issue 3 (4th May 2021)

• Record Type: Journal Article
• Authors: Aytürk, Ezgi; Cham, Heining; Jennings, Patricia A.; Brown, Joshua L.
• Is Part Of: Structural equation modeling. Volume 28:Issue 3(2021)
• Page Start: 410
• Page End: 422
• Publication Date: 2021-05-04
• Subjects: Latent interaction -- categorical data -- latent moderated structural equations; Multivariate analysis -- Periodicals; Social sciences -- Statistical methods -- Periodicals; 519.535
• DOI: 10.1080/10705511.2020.1810047
• Languages: English
• ISSNs: 1070-5511

Abstract

ABSTRACT: Latent moderated structural equations (LMS) is a popular method in estimating latent interaction effects. M plus has implemented a variant of LMS (LMS-cat) that uses categorical confirmatory factor analysis to handle ordered-categorical indicators. We conducted a simulation study to examine the performance of the LMS-cat in varying sample size, interaction effect size, missing data rate and scenario, as well as number and symmetry of item response category conditions. Results showed that the LMS-cat is an excellent method in estimating structural parameters (i.e., interaction effect and lower-order effects). However, it could produce highly biased measurement parameters (i.e., factor loadings, and item category thresholds). We illustrated the LMS-cat by testing the interaction effect between participation in teachers` support activities and that of teachers` counterfactual activities (meditation, meditative movement, vigorous physical exercise) on teachers` sense of self-efficacy.