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Xiaohui Luo; Yueqin Hu – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Intensive longitudinal data has been widely used to examine reciprocal or causal relations between variables. However, these variables may not be temporally aligned. This study examined the consequences and solutions of the problem of temporal misalignment in intensive longitudinal data based on dynamic structural equation models. First the impact…
Descriptors: Structural Equation Models, Longitudinal Studies, Data Analysis, Causal Models
Kamata, Akihito; Bauer, Daniel J. – Structural Equation Modeling: A Multidisciplinary Journal, 2008
The relations among several alternative parameterizations of the binary factor analysis model and the 2-parameter item response theory model are discussed. It is pointed out that different parameterizations of factor analysis model parameters can be transformed into item response model theory parameters, and general formulas are provided.…
Descriptors: Factor Analysis, Data Analysis, Item Response Theory, Correlation
Savalei, Victoria – Structural Equation Modeling: A Multidisciplinary Journal, 2008
Normal theory maximum likelihood (ML) is by far the most popular estimation and testing method used in structural equation modeling (SEM), and it is the default in most SEM programs. Even though this approach assumes multivariate normality of the data, its use can be justified on the grounds that it is fairly robust to the violations of the…
Descriptors: Structural Equation Models, Testing, Factor Analysis, Maximum Likelihood Statistics
Lu, Irene R. R.; Thomas, D. Roland – Structural Equation Modeling: A Multidisciplinary Journal, 2008
This article considers models involving a single structural equation with latent explanatory and/or latent dependent variables where discrete items are used to measure the latent variables. Our primary focus is the use of scores as proxies for the latent variables and carrying out ordinary least squares (OLS) regression on such scores to estimate…
Descriptors: Least Squares Statistics, Computation, Item Response Theory, Structural Equation Models
Bauer, Daniel J. – Structural Equation Modeling: A Multidisciplinary Journal, 2005
To date, finite mixtures of structural equation models (SEMMs) have been developed and applied almost exclusively for the purpose of providing model-based cluster analyses. This type of analysis constitutes a direct application of the model wherein the estimated component distributions of the latent classes are thought to represent the…
Descriptors: Structural Equation Models, Multivariate Analysis, Data Analysis, Evaluation Methods
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