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The Estimation of School Effects
Stephen W. Raudenbush
Michigan State University
JDouglas Willms
University of New Brunswick
The increasing public demand to hold schools accountable for their effects on student outcomes lends urgency to the task of clarifying statistical issues pertaining to studies of school effects. This article considers the specification and estimation of school effects, the variability of effects across schools, and the proportion of variation in student outcomes attributable to differences in school context and practice. We present a statistical model that defines two different types of school effect: one appropriate for parents choosing schools for their children, the second for agencies evaluating school practice. Studies of both types of effect are viewed as quasi-experiments posing formidable obstacles to valid causal inference. A multilevel decomposition of variance within and between schools has important and perhaps counterintuitive implications for school evaluation. The potential for unbiased estimation depends on the type of effect under consideration because the two types of school effect have markedly different data requirements. Commonly used estimators of each effect are shown to be biased and, in some cases, inconsistent. Analyses of survey data from Scotland illustrate the recommended techniques. We conclude with a brief discussion of the role of school evaluation in a broader agenda of research in support of school improvement.
Key Words: multilevel data hierarchical linear models school effects school evaluation causal inference
Journal of Educational and Behavioral Statistics, Vol. 20, No. 4,
307-335 (1995)
DOI: 10.3102/10769986020004307

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