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Lo, Lawrence L.; Molenaar, Peter C. M.; Rovine, Michael – Applied Developmental Science, 2017
Determining the number of factors is a critical first step in exploratory factor analysis. Although various criteria and methods for determining the number of factors have been evaluated in the usual between-subjects R-technique factor analysis, there is still question of how these methods perform in within-subjects P-technique factor analysis. A…
Descriptors: Factor Analysis, Structural Equation Models, Correlation, Sample Size
Phillips, Deborah A.; Anderson, Sara; Gormley, William T., Jr. – Applied Developmental Science, 2018
To examine associations between participation in Tulsa's preschool programs and a set of middle-school attitudes, we used propensity score weighting to compare the Tulsa Public Schools (TPS) pre-K participants and, separately, the Community Action Project (CAP) Head Start participants to students who had attended neither TPS pre-K nor Head Start…
Descriptors: Correlation, Preschool Education, Middle School Students, Comparative Analysis
Wray-Lake, Laura; Metzger, Aaron; Syvertsen, Amy K. – Applied Developmental Science, 2017
Despite recognition that youth civic engagement is multidimensional, different modeling approaches are rarely compared or tested for measurement invariance. Using a diverse sample of 2,467 elementary, middle, and high school-aged youth, we measured eight dimensions of civic engagement: social responsibility values, informal helping, political…
Descriptors: Citizen Participation, Elementary School Students, Middle School Students, High School Students