Assessing Measurement Invariance in Multiple-Group Latent Profile Analysis. Issue 3 (4th May 2018)

• Record Type: Journal Article
• Authors: Olivera-Aguilar, Margarita; Rikoon, Samuel H.
• Is Part Of: Structural equation modeling. Volume 25:Issue 3(2018)
• Page Start: 439
• Page End: 452
• Publication Date: 2018-05-04
• Subjects: latent profile analysis -- measurement invariance -- multiple-group analysis; Multivariate analysis -- Periodicals; Social sciences -- Statistical methods -- Periodicals; 519.535
• DOI: 10.1080/10705511.2017.1408015
• Languages: English
• ISSNs: 1070-5511

Abstract

Abstract : The study of measurement invariance in latent profile analysis (LPA) indicates whether the latent profiles differ across known subgroups (e.g., gender). The purpose of the present study was to examine the impact of noninvariance on the relative bias of LPA parameter estimates and on the ability of the likelihood ratio test (LRT) and information criteria statistics to reject the hypothesis of invariance. A Monte Carlo simulation study was conducted in which noninvariance was defined as known group differences in the indicator means in each profile. Results indicated that parameter estimates were biased in conditions with medium and large noninvariance. The LRT and AIC detected noninvariance in most conditions with small sample sizes, while the BIC and adjusted BIC needed larger sample sizes to detect noninvariance. Implications of the results are discussed along with recommendations for future research.