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Andrea Hasl; Manuel Voelkle; Charles Driver; Julia Kretschmann; Martin Brunner – Structural Equation Modeling: A Multidisciplinary Journal, 2024
To examine developmental processes, intervention effects, or both, longitudinal studies often aim to include measurement intervals that are equally spaced for all participants. In reality, however, this goal is hardly ever met. Although different approaches have been proposed to deal with this issue, few studies have investigated the potential…
Descriptors: Foreign Countries, Elementary School Students, Secondary School Students, Student Promotion
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Grimm, Kevin J.; Ram, Nilam – Structural Equation Modeling: A Multidisciplinary Journal, 2009
Nonlinear growth curves or growth curves that follow a specified nonlinear function in time enable researchers to model complex developmental patterns with parameters that are easily interpretable. In this article we describe how a variety of sigmoid curves can be fit using the M"plus" structural modeling program and the nonlinear…
Descriptors: Structural Equation Models, Statistical Analysis, Computer Software, Longitudinal Studies
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Coffman, Donna L.; Millsap, Roger E. – Structural Equation Modeling: A Multidisciplinary Journal, 2006
The usefulness of assessing individual fit in latent growth curve models was examined. The study used simulated data based on an unconditional and a conditional latent growth curve model with a linear component and a small quadratic component and a linear model was fit to the data. Then the overall fit of linear and quadratic models to these data…
Descriptors: Structural Equation Models, Evaluation Methods, Goodness of Fit, Individual Development