Detecting Measurement Noninvariance with Continuous Indicators Using Three Different Statistical Methods under the Framework of Latent Variable Modeling. Issue 4 (4th July 2022)

• Record Type: Journal Article
• Authors: Zhang, Mingcai; Yang, Lihong
• Is Part Of: Structural equation modeling. Volume 29:Issue 4(2022)
• Page Start: 550
• Page End: 568
• Publication Date: 2022-07-04
• Subjects: Latent variable modelling -- measurement noninvariance -- reference indicator; Multivariate analysis -- Periodicals; Social sciences -- Statistical methods -- Periodicals; 519.535
• DOI: 10.1080/10705511.2021.2021533
• Languages: English
• ISSNs: 1070-5511

Abstract

Abstract: Under the framework of Latent Variable Modelling, three statistical methods, namely, the free baseline method (FR), the Benjamini-Hochberg method (B–H), and the alignment method (AM), were applied to identify the noninvariant measurement parameters at the indicator level through a simulation study. Model noninvariance was manipulated through varying the locations, degrees and magnitudes of noninvariant parameters with different sample sizes. As a result, the B-H method was discovered to possess a higher power rate in detecting noninvariant parameters than the other two methods, and the AM method performed the best in controlling the type I error rates in the process of parameter estimation. Comparatively speaking, the FR method performed the worst in almost all situations due to the choice of a fixed noninvariant reference indicator. The suggestions on which method is better used for model noninvariance detection was discussed and elaborated.