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On Latent Change Model Choice in Longitudinal Studies
Authors:Tenko Raykov  Anna Zajacova
Institution:1. Michigan State University;2. University of Wyoming
Abstract:An interval estimation procedure for proportion of explained observed variance in latent curve analysis is discussed, which can be used as an aid in the process of choosing between linear and nonlinear models. The method allows obtaining confidence intervals for the R 2 indexes associated with repeatedly followed measures in longitudinal studies. In addition to facilitating evaluation of local model fit, the approach is helpful for purposes of differentiating between plausible models stipulating different patterns of change over time, and in particular in empirical situations characterized by large samples and high statistical power. The procedure is also applicable in cross-sectional studies, as well as with general structural equation models. The method is illustrated using data from a nationally representative study of older adults.
Keywords:confidence interval  latent change analysis  linear change  model choice  nonlinear change
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