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Direct linkZhang, 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
Lanza, Stephanie T.; Collins, Linda M.; Lemmon, David R.; Schafer, Joseph L. – Structural Equation Modeling: A Multidisciplinary Journal, 2007
Latent class analysis (LCA) is a statistical method used to identify a set of discrete, mutually exclusive latent classes of individuals based on their responses to a set of observed categorical variables. In multiple-group LCA, both the measurement part and structural part of the model can vary across groups, and measurement invariance across…
Descriptors: Structural Equation Models, Syntax, Drinking, Statistical Analysis
Ferrer, Emilio; McArdle, John – Structural Equation Modeling: A Multidisciplinary Journal, 2003
Structural equation models are presented as alternative models for examining longitudinal data. The models include (a) a cross-lagged regression model, (b) a factor model based on latent growth curves, and (c) a dynamic model based on latent difference scores. The illustrative data are on motivation and perceived competence of students during…
Descriptors: Models, Data Analysis, Structural Equation Models, Longitudinal Studies
