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Geiser, Christian; Eid, Michael; West, Stephen G.; Lischetzke, Tanja; Nussbeck, Fridtjof W. – Structural Equation Modeling: A Multidisciplinary Journal, 2012
Multimethod data analysis is a complex procedure that is often used to examine the degree to which different measures of the same construct converge in the assessment of this construct. Several authors have called for a greater understanding of the definition and meaning of method effects in different models for multimethod data. In this article,…
Descriptors: Structural Equation Models, Factor Analysis, Multitrait Multimethod Techniques, Comparative Analysis
Castro-Schilo, Laura; Widaman, Keith F.; Grimm, Kevin J. – Structural Equation Modeling: A Multidisciplinary Journal, 2013
In 1959, Campbell and Fiske introduced the use of multitrait-multimethod (MTMM) matrices in psychology, and for the past 4 decades confirmatory factor analysis (CFA) has commonly been used to analyze MTMM data. However, researchers do not always fit CFA models when MTMM data are available; when CFA modeling is used, multiple models are available…
Descriptors: Multitrait Multimethod Techniques, Factor Analysis, Structural Equation Models, Monte Carlo Methods
LaGrange, Beth; Cole, David A. – Structural Equation Modeling: A Multidisciplinary Journal, 2008
This article examines 4 approaches for explaining shared method variance, each applied to a longitudinal trait-state-occasion (TSO) model. Many approaches have been developed to account for shared method variance in multitrait-multimethod (MTMM) data. Some of these MTMM approaches (correlated method, orthogonal method, correlated method minus one,…
Descriptors: Structural Equation Models, Longitudinal Studies, Multitrait Multimethod Techniques, Correlation
Marsh, Herbert W.; Nagengast, Benjamin; Morin, Alexandre J. S.; Parada, Roberto H.; Craven, Rhonda G.; Hamilton, Linda R. – Journal of Educational Psychology, 2011
Existing research posits multiple dimensions of bullying and victimization but has not identified well-differentiated facets of these constructs that meet standards of good measurement: goodness of fit, measurement invariance, lack of differential item functioning, and well-differentiated factors that are not so highly correlated as to detract…
Descriptors: Locus of Control, Test Bias, Bullying, Structural Equation Models