Mediated Effects with the Parallel Process Latent Growth Model: An Evaluation of Methods for Testing Mediation in the Presence of Nonnormal Data. Issue 1 (2nd January 2016)

• Record Type: Journal Article
• Authors: Koo, Namwook; Leite, Walter L.; Algina, James
• Is Part Of: Structural equation modeling. Volume 23:Issue 1(2016)
• Page Start: 32
• Page End: 44
• Publication Date: 2016-01-02
• Subjects: asymmetric confidence limits -- bias-corrected bootstrap -- longitudinal mediation -- nonnormality -- parallel process latent growth model -- Sobel's test; Multivariate analysis -- Periodicals; Social sciences -- Statistical methods -- Periodicals; 519.535
• DOI: 10.1080/10705511.2014.959419
• Languages: English
• ISSNs: 1070-5511

Abstract

Abstract : This Monte Carlo simulation study investigated the impact of nonnormality on estimating and testing mediated effects with the parallel process latent growth model and 3 popular methods for testing the mediated effect (i.e., Sobel's test, the asymmetric confidence limits, and the bias-corrected bootstrap). It was found that nonnormality had little effect on the estimates of the mediated effect, standard errors, empirical Type I error, and power rates in most conditions. In terms of empirical Type I error and power rates, the bias-corrected bootstrap performed best. Sobel's test produced very conservative Type I error rates when the estimated mediated effect and standard error had a relationship, but when the relationship was weak or did not exist, the Type I error was closer to the nominal .05 value.