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Latent Growth Curve Models: Tracking Changes Over Time

WebLatent Growth Curve Modeling: A Brief History and Overview Historically, growth curve models(e.g., Potthoff & Roy, 1964) have been used to model longitudinal data in which repeated measurements are observed for some outcome variable at a number of occasions. The latent growth curve approach is rooted in the exploratory factor analysis(EFA) gabby thornton coffee table

Identifying typical trajectories in longitudinal data: modelling

Latent growth curve analysis (LGCA) is a powerful technique that is based on structural equation modeling. Another approach, which will not be directly discussed here, is multilevel modeling, which employs the statistical techniques of general linear regression and specifies fixed and random effects. LGCA, on the … See more There are several statistical approaches that can be used to analyze trajectories of change in a variable or variables over time. The simplest approach is to describe … See more WebThe latent growth curve model (LGCM) is a useful tool in analyzing longitudinal data. It is particularly suitable for gerontological research because the LGCM can track the trajectories and changes of phenomena (e.g., physical health and psychological well-being) over time. Specifically, the LGCM co … WebStatistical Analysis With Latent Variables A General Modeling Framework (Continued) • Factor analysis models • Structural equation models • Growth curve models • Multilevel models • Latent class models • Mixture models • Discrete-time survival models • Missing data models Models That Use Latent Variables gabby tonal