Title | Preliminary Detection of Relations Among Dynamic Processes With Two-Occasion Data |
Publication Type | Journal Article |
Year of Publication | 2016 |
Authors | Henk, CM, Castro-Schilo, L |
Journal | Structural Equation Modeling |
Volume | 23 |
Issue | 2 |
Pagination | 180-193 |
Keywords | Methodology |
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, and Card, 2007; Selig and Preacher, 2009). 2015, Routledge. All rights reserved. |
Notes | Export Date: 9 September 2015 Article in Press |
URL | http://www.scopus.com/inward/record.url?eid=2-s2.0-84939133366andpartnerID=40andmd5=1d363cc0f73ccff4fa0eda079882d1f0 |
DOI | 10.1080/10705511.2015.1030022 |
Endnote Keywords | change scores/difference scores/latent change score model/latent change score model/two-occasion data |
Endnote ID | 999999 |
Citation Key | 8402 |