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Park, Sira; Holloway, Susan D. – Journal of Educational Research, 2017
Policymakers view parental involvement (PI) as a crucial component of school reform efforts, but evidence of its effect on student achievement is equivocal. Using the Early Childhood Longitudinal Study-Kindergarten Cohort dataset, we examined the long-term impact on student- and school-level achievement of three types of school-based PI: PI to…
Descriptors: Longitudinal Studies, Parent Participation, Hierarchical Linear Modeling, Reading Achievement
Jak, Suzanne; Oort, Frans J.; Dolan, Conor V. – Structural Equation Modeling: A Multidisciplinary Journal, 2013
We present a test for cluster bias, which can be used to detect violations of measurement invariance across clusters in 2-level data. We show how measurement invariance assumptions across clusters imply measurement invariance across levels in a 2-level factor model. Cluster bias is investigated by testing whether the within-level factor loadings…
Descriptors: Statistical Bias, Measurement, Structural Equation Models, Hierarchical Linear Modeling
Morin, Alexandre J. S.; Marsh, Herbert W.; Nagengast, Benjamin; Scalas, L. Francesca – Journal of Experimental Education, 2014
Many classroom climate studies suffer from 2 critical problems: They (a) treat climate as a student-level (L1) variable in single-level analyses instead of a classroom-level (L2) construct in multilevel analyses; and (b) rely on manifest-variable models rather than on latent-variable models that control measurement error at L1 and L2, and sampling…
Descriptors: Classroom Environment, Hierarchical Linear Modeling, Structural Equation Models, Grade 5

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