Methodological Issues in the Application of the Latent Growth Curve Model

Abstract

Latent growth curve analysis (McArdle, 1986, 1988; Meredith & Tisak, 1990; Willett & Sayer, 1994) is well suited to analyze systematic change in longitudinal data collected from a panel design. It represents outcome variables explicitly as a function of time and other measures. Specifically, latent growth curve analysis is a Statistical technique to estimate the Parameters that represent the growth curves that are assumed to have given rise to the structure of the repeatedly measured outcome variable over time. Growth curve analysis can be applied just to get a (unconditional) description of the mean growth over a certain period of time. However, the emphasis of this technique lies in explanation of differences between subjects in the parameters describing the growth curves; in other words, in the systematic inter-individual differences in intra-individual change.KeywordsMeasurement InvarianceFactorial InvarianceGrowth Curve ModelMeasurement OccasionLatent Growth CurveThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.