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Li, Angran; Fischer, Mary J. – Sociology of Education, 2017
This article examines the relationship between parental networks and parental school involvement during the elementary school years. Using a large, nationally representative data set of elementary school students--the Early Childhood Longitudinal Study-Kindergarten Cohort--and contextual data from the 2000 U.S. Census, our multilevel analysis…
Descriptors: Correlation, Social Networks, Network Analysis, Elementary School Students
Sun, Shuyan; Pan, Wei – International Journal of Research & Method in Education, 2014
As applications of multilevel modelling in educational research increase, researchers realize that multilevel data collected in many educational settings are often not purely nested. The most common multilevel non-nested data structure is one that involves student mobility in longitudinal studies. This article provides a methodological review of…
Descriptors: Statistical Analysis, Hierarchical Linear Modeling, Longitudinal Studies, Educational Research
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
Youn, Minjong – Early Child Development and Care, 2016
This study employed the concept of teachers' sense of responsibility for students' learning to examine the extent to which the gap in math learning growth is reduced and whether such attitudes can improve children's learning outcomes to a degree that is above and beyond their expected achievement relative to their initial academic skills. Analysis…
Descriptors: Teacher Influence, Teacher Attitudes, Outcomes of Education, Teacher Student Relationship
Shin, Yongyun; Raudenbush, Stephen W. – Grantee Submission, 2013
This paper extends single-level missing data methods to efficient estimation of a "Q"-level nested hierarchical general linear model given ignorable missing data with a general missing pattern at any of the "Q" levels. The key idea is to reexpress a desired hierarchical model as the joint distribution of all variables including…
Descriptors: Hierarchical Linear Modeling, Computation, Statistical Bias, Body Composition
Luo, Wen; Azen, Razia – Journal of Educational and Behavioral Statistics, 2013
Dominance analysis (DA) is a method used to evaluate the relative importance of predictors that was originally proposed for linear regression models. This article proposes an extension of DA that allows researchers to determine the relative importance of predictors in hierarchical linear models (HLM). Commonly used measures of model adequacy in…
Descriptors: Predictor Variables, Hierarchical Linear Modeling, Statistical Analysis, Regression (Statistics)
Han, Jisu; Schlieber, Marisa; Gregory, Bradley – Journal of Education for Students Placed at Risk, 2017
This study used data from the Head Start Family and Child Experiences Survey (FACES) 2009 4-year-old cohort to examine associations among family characteristics, home and classroom environments, and the emergent literacy skills of Head Start children. Results from hierarchical linear models suggest that both family and classroom contexts play a…
Descriptors: Oral Language, Language Skills, Vocabulary Development, Expressive Language