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Direct linkKim, Minjung; Hsu, Hsien-Yuan – Journal of Educational and Behavioral Statistics, 2019
Given the natural hierarchical structure in school-setting data, multilevel modeling (MLM) has been widely employed in education research using a number of different statistical software packages. The purpose of this article is to review a recent feature of Stat-JR, the statistical analysis assistants (SAAs) embedded in Stat-JR (Version 1.0.5),…
Descriptors: Hierarchical Linear Modeling, Statistical Analysis, Computer Software, Computer Software Evaluation
Liu, Hongqiang; Van Damme, Jan; Gielen, Sarah; Van Den Noortgate, Wim – British Educational Research Journal, 2015
School composition effects have been consistently verified, but few studies ever attempted to study how school composition affects school achievement. Based on prior research findings, we employed multilevel mediation modeling to examine whether school processes mediate the effect of school composition upon school outcomes based on the data of 28…
Descriptors: School Demography, Hierarchical Linear Modeling, Educational Resources, Educational Opportunities
Castellano, Katherine E.; Rabe-Hesketh, Sophia; Skrondal, Anders – Journal of Educational and Behavioral Statistics, 2014
Investigations of the effects of schools (or teachers) on student achievement focus on either (1) individual school effects, such as value-added analyses, or (2) school-type effects, such as comparisons of charter and public schools. Controlling for school composition by including student covariates is critical for valid estimation of either kind…
Descriptors: Hierarchical Linear Modeling, Context Effect, Economics, Educational Research
Jacob, Robin T.; Goddard, Roger D.; Kim, Eun Sook – Educational Evaluation and Policy Analysis, 2014
It is often difficult and costly to obtain individual-level student achievement data, yet, researchers are frequently reluctant to use school-level achievement data that are widely available from state websites. We argue that public-use aggregate school-level achievement data are, in fact, sufficient to address a wide range of evaluation questions…
Descriptors: Academic Achievement, Data, Information Utilization, Educational Assessment
Creech, Leah Renee; Sweeder, Ryan D. – CBE - Life Sciences Education, 2012
This study examined the historical performance of students at Michigan State University in 12 life sciences courses over 13 yr to find variables impacting student success. Hierarchical linear modeling predicted 25.0-62.8% of the variance in students' grades in the courses analyzed. The primary predictor of a student's course grade was his or her…
Descriptors: Academic Achievement, Majors (Students), Grade Point Average, Biochemistry
Whitehurst, Grover J.; Chingos, Matthew M.; Gallaher, Michael R. – Brookings Institution, 2013
School districts occupy center stage in education reform in the U.S. They manage nearly all public funding and are frequently the locus of federal and state reform initiatives, e.g., instituting meaningful teacher evaluation systems. Financial compensation for district leaders is high, with many being paid more than the chief state school officers…
Descriptors: School Districts, Superintendents, Academic Achievement, Influences
Youngs, Peter; Frank, Kenneth; Thum, Yeow Meng; Low, Mark – Yearbook of the National Society for the Study of Education, 2012
In this chapter, the authors develop a theory to explain the effects of mentoring and induction activities on new teachers' commitment, instructional quality, and effectiveness, and they describe how utility functions can express variation in these outcomes. Then they explicate the role of three-level models (i.e., with random effects) in…
Descriptors: Academic Achievement, Teacher Effectiveness, Social Behavior, Testing
