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Alexander Robitzsch; Oliver Lüdtke – Structural Equation Modeling: A Multidisciplinary Journal, 2025
The random intercept cross-lagged panel model (RICLPM) decomposes longitudinal associations between two processes X and Y into stable between-person associations and temporal within-person changes. In a recent study, Bailey et al. demonstrated through a simulation study that the between-person variance components in the RICLPM can occur only due…
Descriptors: Longitudinal Studies, Correlation, Time, Simulation
Xiao Liu; Lijuan Wang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
In parallel process latent growth curve mediation models, the mediation pathways from treatment to the intercept or slope of outcome through the intercept or slope of mediator are often of interest. In this study, we developed causal mediation analysis methods for these mediation pathways. Particularly, we provided causal definitions and…
Descriptors: Causal Models, Mediation Theory, Psychological Studies, Educational Research
Finch, W. Holmes; French, Brian F. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
The purpose of this simulation study was to assess the performance of latent variable models that take into account the complex sampling mechanism that often underlies data used in educational, psychological, and other social science research. Analyses were conducted using the multiple indicator multiple cause (MIMIC) model, which is a flexible…
Descriptors: Causal Models, Computation, Data, Sampling
Bollen, Kenneth A.; Davis, Walter R. – Structural Equation Modeling: A Multidisciplinary Journal, 2009
We discuss the identification, estimation, and testing of structural equation models that have causal indicators. We first provide 2 rules of identification that are particularly helpful in models with causal indicators--the 2C emitted paths rule and the exogenous X rule. We demonstrate how these rules can help us distinguish identified from…
Descriptors: Structural Equation Models, Testing, Identification, Statistical Significance