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Direct linkCoulombe, Patrick; Selig, James P.; Delaney, Harold D. – International Journal of Behavioral Development, 2016
Researchers often collect longitudinal data to model change over time in a phenomenon of interest. Inevitably, there will be some variation across individuals in specific time intervals between assessments. In this simulation study of growth curve modeling, we investigate how ignoring individual differences in time points when modeling change over…
Descriptors: Individual Differences, Longitudinal Studies, Simulation, Change
Hertzog, Christopher; von Oertzen, Timo; Ghisletta, Paolo; Lindenberger, Ulman – Structural Equation Modeling: A Multidisciplinary Journal, 2008
We evaluated the statistical power of single-indicator latent growth curve models to detect individual differences in change (variances of latent slopes) as a function of sample size, number of longitudinal measurement occasions, and growth curve reliability. We recommend the 2 degree-of-freedom generalized test assessing loss of fit when both…
Descriptors: Sample Size, Error of Measurement, Individual Differences, Statistical Analysis
