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Ke-Hai Yuan; Ling Ling; Zhiyong Zhang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Data in social and behavioral sciences typically contain measurement errors and do not have predefined metrics. Structural equation modeling (SEM) is widely used for the analysis of such data, where the scales of the manifest and latent variables are often subjective. This article studies how the model, parameter estimates, their standard errors…
Descriptors: Structural Equation Models, Computation, Social Science Research, Error of Measurement
Raykov, Tenko; Marcoulides, George A. – Structural Equation Modeling: A Multidisciplinary Journal, 2013
A latent variable modeling approach is outlined that can be used for meta-analysis of reliability coefficients of multicomponent measuring instruments. Important limitations of efforts to combine composite reliability findings across multiple studies are initially pointed out. A reliability synthesis procedure is discussed that is based on…
Descriptors: Meta Analysis, Reliability, Structural Equation Models, Error of Measurement
Cheung, Mike
W.-L. – Structural Equation Modeling: A Multidisciplinary Journal, 2013
Structural equation modeling (SEM) is now a generic modeling framework for many multivariate techniques applied in the social and behavioral sciences. Many statistical models can be considered either as special cases of SEM or as part of the latent variable modeling framework. One popular extension is the use of SEM to conduct linear mixed-effects…
Descriptors: Structural Equation Models, Maximum Likelihood Statistics, Guidelines, Multivariate Analysis
Cheung, Mike W. -L. – Structural Equation Modeling: A Multidisciplinary Journal, 2010
Meta-analysis is the statistical analysis of a collection of analysis results from individual studies, conducted for the purpose of integrating the findings. Structural equation modeling (SEM), on the other hand, is a multivariate technique for testing hypothetical models with latent and observed variables. This article shows that fixed-effects…
Descriptors: Structural Equation Models, Syntax, Effect Size, Meta Analysis
Cheung, Mike W. L.; Chan, Wai – Structural Equation Modeling: A Multidisciplinary Journal, 2009
Structural equation modeling (SEM) is widely used as a statistical framework to test complex models in behavioral and social sciences. When the number of publications increases, there is a need to systematically synthesize them. Methodology of synthesizing findings in the context of SEM is known as meta-analytic SEM (MASEM). Although correlation…
Descriptors: Structural Equation Models, Simulation, Social Sciences, Correlation
Price, Larry R.; Laird, Angela R.; Fox, Peter T.; Ingham, Roger J. – Structural Equation Modeling: A Multidisciplinary Journal, 2009
The aims of this study were to present a method for developing a path analytic network model using data acquired from positron emission tomography. Regions of interest within the human brain were identified through quantitative activation likelihood estimation meta-analysis. Using this information, a "true" or population path model was then…
Descriptors: Sample Size, Monte Carlo Methods, Structural Equation Models, Markov Processes