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Ghisletta, Paolo; McArdle, John J. – Structural Equation Modeling: A Multidisciplinary Journal, 2012
In recent years the use of the latent curve model (LCM) among researchers in social sciences has increased noticeably, probably thanks to contemporary software developments and the availability of specialized literature. Extensions of the LCM, like the the latent change score model (LCSM), have also increased in popularity. At the same time, the R…
Descriptors: Statistical Analysis, Structural Equation Models, Computation, Computer Software
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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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Willoughby, Michael; Vandergrift, Nathan; Blair, Clancy; Granger, Douglas A. – Structural Equation Modeling: A Multidisciplinary Journal, 2007
This study introduces a novel application of structural equation modeling (SEM) for the analysis of cortisol data that are collected using a pre-post-post design. By way of an extended example, an SEM model is developed that permits an examination of both the overall level of cortisol, as well as changes in cortisol (reactivity and regulation), as…
Descriptors: Disadvantaged Youth, Structural Equation Models, Cognitive Ability, Preschool Children