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Direct linkYuan, Ke-Hai; Kano, Yutaka – Journal of Educational and Behavioral Statistics, 2018
Meta-analysis plays a key role in combining studies to obtain more reliable results. In social, behavioral, and health sciences, measurement units are typically not well defined. More meaningful results can be obtained by standardizing the variables and via the analysis of the correlation matrix. Structural equation modeling (SEM) with the…
Descriptors: Meta Analysis, Structural Equation Models, Maximum Likelihood Statistics, Least Squares Statistics
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
Furlow, Carolyn F.; Beretvas, S. Natasha – Psychological Methods, 2005
Three methods of synthesizing correlations for meta-analytic structural equation modeling (SEM) under different degrees and mechanisms of missingness were compared for the estimation of correlation and SEM parameters and goodness-of-fit indices by using Monte Carlo simulation techniques. A revised generalized least squares (GLS) method for…
Descriptors: Rejection (Psychology), Monte Carlo Methods, Least Squares Statistics, Correlation
