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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
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Xie, Jun; Bentler, Peter M. – Structural Equation Modeling: A Multidisciplinary Journal, 2003
Covariance structure models are applied to gene expression data using a factor model, a path model, and their combination. The factor model is based on a few factors that capture most of the expression information. A common factor of a group of genes may represent a common protein factor for the transcript of the co-expressed genes, and hence, it…
Descriptors: Path Analysis, Genetics, Structural Equation Models, Factor Analysis
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DiStefano, Christine; Motl, Robert W. – Structural Equation Modeling: A Multidisciplinary Journal, 2006
This article used multitrait-multimethod methodology and covariance modeling for an investigation of the presence and correlates of method effects associated with negatively worded items on the Rosenberg Self-Esteem (RSE) scale (Rosenberg, 1989) using a sample of 757 adults. Results showed that method effects associated with negative item phrasing…
Descriptors: Adults, Correlation, Self Esteem, Surveys