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Ming-Chi Tseng – Structural Equation Modeling: A Multidisciplinary Journal, 2025
This study aims to estimate the latent interaction effect in the CLPM model through a two-step multiple imputation analysis. The estimation of within x within and between x within latent interaction under the CLPM model framework is compared between the one-step Bayesian LMS method and the two-step multiple imputation analysis through a simulation…
Descriptors: Guidelines, Bayesian Statistics, Self Esteem, Depression (Psychology)
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Grimm, Kevin J. – Structural Equation Modeling: A Multidisciplinary Journal, 2012
Latent difference score (LDS) models combine benefits derived from autoregressive and latent growth curve models allowing for time-dependent influences and systematic change. The specification and descriptions of LDS models include an initial level of ability or trait plus an accumulation of changes. A limitation of this specification is that the…
Descriptors: Structural Equation Models, Time, Change, Coding
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Bray, Bethany C.; Lanza, Stephanie T.; Collins, Linda M. – Structural Equation Modeling: A Multidisciplinary Journal, 2010
To understand one developmental process, it is often helpful to investigate its relations with other developmental processes. Statistical methods that model development in multiple processes simultaneously over time include latent growth curve models with time-varying covariates, multivariate latent growth curve models, and dual trajectory models.…
Descriptors: Structural Equation Models, Development, Statistical Analysis, Drinking
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Zhang, Zhiyong; Lai, Keke; Lu, Zhenqiu; Tong, Xin – Structural Equation Modeling: A Multidisciplinary Journal, 2013
Despite the widespread popularity of growth curve analysis, few studies have investigated robust growth curve models. In this article, the "t" distribution is applied to model heavy-tailed data and contaminated normal data with outliers for growth curve analysis. The derived robust growth curve models are estimated through Bayesian…
Descriptors: Structural Equation Models, Bayesian Statistics, Statistical Inference, Statistical Distributions
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Grimm, Kevin J.; Widaman, Keith F. – Structural Equation Modeling: A Multidisciplinary Journal, 2010
Several alternatives are available for specifying the residual structure in latent growth curve modeling. Two specifications involve uncorrelated residuals and represent the most commonly used residual structures. The first, building on repeated measures analysis of variance and common specifications in multilevel models, forces residual variances…
Descriptors: Structural Equation Models, Statistical Analysis, Measurement, Reading Achievement
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Dolan, Conor V.; Schmittmann, Verena D.; Lubke, Gitta H.; Neale, Michael C. – Structural Equation Modeling: A Multidisciplinary Journal, 2005
A linear latent growth curve mixture model is presented which includes switching between growth curves. Switching is accommodated by means of a Markov transition model. The model is formulated with switching as a highly constrained multivariate mixture model and is fitted using the freely available Mx program. The model is illustrated by analyzing…
Descriptors: Drinking, Adolescents, Evaluation Methods, Structural Equation Models