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Chuenjai Sukpan; Rebecca M. Kuiper – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The (Random Intercept) Cross-Lagged Panel Model ((RI-)CLPM) is increasingly used in psychology and related fields to assess the longitudinal relationship of two or more variables on each other. Researchers are interested in the question which of the lagged effects is causally dominant receives considerable attention. However, currently used…
Descriptors: Causal Models, Psychological Studies, Multivariate Analysis, Cognitive Mapping
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
Walter P. Vispoel; Hyeryung Lee; Hyeri Hong – Structural Equation Modeling: A Multidisciplinary Journal, 2024
We demonstrate how to analyze complete multivariate generalizability theory (GT) designs within structural equation modeling frameworks that encompass both individual subscale scores and composites formed from those scores. Results from numerous analyses of observed scores obtained from respondents who completed the recently updated form of the…
Descriptors: Structural Equation Models, Multivariate Analysis, Generalizability Theory, College Students
Dayoung Lee; Guangjian Zhang; Shanhong Luo – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The circumplex model posits a circular representation of affect and some personality traits. There is an increasing need to examine the viability of the circumplex model with multivariate time series data collected on the same individuals due to the development of new data collection methods such as smartphone applications and wearable sensors.…
Descriptors: Research Methodology, Affective Measures, Family Relationship, Multivariate Analysis
James Ohisei Uanhoro – Structural Equation Modeling: A Multidisciplinary Journal, 2024
We present a method for Bayesian structural equation modeling of sample correlation matrices as correlation structures. The method transforms the sample correlation matrix to an unbounded vector using the matrix logarithm function. Bayesian inference about the unbounded vector is performed assuming a multivariate-normal likelihood, with a mean…
Descriptors: Bayesian Statistics, Structural Equation Models, Correlation, Monte Carlo Methods
C. J. Van Lissa; M. Garnier-Villarreal; D. Anadria – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Latent class analysis (LCA) refers to techniques for identifying groups in data based on a parametric model. Examples include mixture models, LCA with ordinal indicators, and latent class growth analysis. Despite its popularity, there is limited guidance with respect to decisions that must be made when conducting and reporting LCA. Moreover, there…
Descriptors: Multivariate Analysis, Structural Equation Models, Open Source Technology, Computation
Walter P. Vispoel; Hyeri Hong; Hyeryung Lee – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Although generalizability theory (GT) designs typically are analyzed using analysis of variance (ANOVA) procedures, they also can be integrated into structural equation models (SEMs). In this tutorial, we review basic concepts for conducting univariate and multivariate GT analyses and demonstrate advantages of doing such analyses within SEM…
Descriptors: Structural Equation Models, Self Concept Measures, Self Esteem, Generalizability Theory