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Choosing the Optimal Number of Factors in Exploratory Factor Analysis: A Model Selection Perspective
Preacher, Kristopher J.; Zhang, Guangjian; Kim, Cheongtag; Mels, Gerhard – Multivariate Behavioral Research, 2013
A central problem in the application of exploratory factor analysis is deciding how many factors to retain ("m"). Although this is inherently a model selection problem, a model selection perspective is rarely adopted for this task. We suggest that Cudeck and Henly's (1991) framework can be applied to guide the selection process.…
Descriptors: Factor Analysis, Models, Selection, Goodness of Fit
Grimm, Kevin J.; Pianta, Robert C.; Konold, Timothy – Multivariate Behavioral Research, 2009
Multitrait-multimethod (MTMM) confirmatory factor models were combined with longitudinal structural equation models to examine trait and method stability over time. A longitudinal correlated-trait correlated-method (CT-CM) model allowed for the study of trait and method variance in observed scores over time. Longitudinal measurement invariance was…
Descriptors: Multitrait Multimethod Techniques, Structural Equation Models, Longitudinal Studies, Children
Van Horn, M. Lee; Fagan, Abigail A.; Jaki, Thomas; Brown, Eric C.; Hawkins, J. David; Arthur, Michael W.; Abbott, Robert D.; Catalano, Richard F. – Multivariate Behavioral Research, 2008
There is evidence to suggest that the effects of behavioral interventions may be limited to specific types of individuals, but methods for evaluating such outcomes have not been fully developed. This study proposes the use of finite mixture models to evaluate whether interventions, and, specifically, group randomized trials, impact participants…
Descriptors: Intervention, Adolescents, Models, Behavior Problems