Multivariate Latent Growth Modeling: Issues on Preliminary Data Analyses

Abstract

Multivariate latent growth modeling (multivariate LGM) provides a flexible data analytic framework for representing and assessing cross-domain (i.e., between-constructs) relationships in intraindividual changes over time, which also allows incorporation of multiple levels of analysis. Using the chapter by Cortina, Pant, and Smith-Darden (this volume) as a point of departure, this chapter discusses important preliminary data analysis and interpretation issues prior to performing multivariate LGM analyses.

Citation

Chan, D. (2005), "Multivariate Latent Growth Modeling: Issues on Preliminary Data Analyses", Dansereau, F. and Yammarino, F.J. (Ed.) Multi-Level Issues in Strategy and Methods (Research in Multi-Level Issues, Vol. 4), Emerald Group Publishing Limited, Leeds, pp. 319-334. https://doi.org/10.1016/S1475-9144(05)04014-2