Preliminary Detection of Relations Among Dynamic Processes With Two-Occasion Data. Issue 2 (3rd March 2016)

• Record Type: Journal Article
• Authors: Henk, Corinne M.; Castro-Schilo, Laura
• Is Part Of: Structural equation modeling. Volume 23:Issue 2(2016)
• Page Start: 180
• Page End: 193
• Publication Date: 2016-03-03
• Subjects: change scores -- difference scores -- latent change score model -- two-occasion data; Multivariate analysis -- Periodicals; Social sciences -- Statistical methods -- Periodicals; 519.535
• DOI: 10.1080/10705511.2015.1030022
• Languages: English
• ISSNs: 1070-5511

Abstract

Abstract : Most novel analytic methods for longitudinal data are applicable to studies spanning three time-points of data at a minimum, whereas methods for two-occasion data have garnered comparatively little attention. Here, we address this limitation by introducing the two-wave latent change score (2W-LCS) model, a technique appropriate for preliminary detection of relations among dynamic processes with two-occasion data. The 2W-LCS model is well suited for the investigation of hypotheses in which changes in a construct are posited as predictors of changes in another construct. In an empirical illustration using data of elderly Hispanics from the Health and Retirement Study, we demonstrate how the 2W-LCS model provides the best match to theories rooted in changes, and highlight the advantages of this approach over other modeling alternatives (i.e., Little, Preacher, Selig, & Card, 2007; Selig & Preacher, 2009).