journal article Mar 01, 2007

Using Covariates to Improve Precision for Studies That Randomize Schools to Evaluate Educational Interventions

View at Publisher Save 10.3102/0162373707299550
Abstract
This article examines how controlling statistically for baseline covariates, especially pretests, improves the precision of studies that randomize schools to measure the impacts of educational interventions on student achievement. Empirical findings from five urban school districts indicate that (1) pretests can reduce the number of randomized schools needed for a given level of precision to about half of what would be needed otherwise for elementary schools, one fifth for middle schools, and one tenth for high schools, and (2) school-level pretests are as effective in this regard as student-level pretests. Furthermore, the precision-enhancing power of pretests (3) declines only slightly as the number of years between the pretest and posttests increases; (4) improves only slightly with pretests for more than 1 baseline year; and (5) is substantial, even when the pretest differs from the posttest. The article compares these findings with past research and presents an approach for quantifying their uncertainty.
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References
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Cited By
181
Metrics
181
Citations
28
References
Details
Published
Mar 01, 2007
Vol/Issue
29(1)
Pages
30-59
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Cite This Article
Howard S. Bloom, Lashawn Richburg-Hayes, Alison Rebeck Black (2007). Using Covariates to Improve Precision for Studies That Randomize Schools to Evaluate Educational Interventions. Educational Evaluation and Policy Analysis, 29(1), 30-59. https://doi.org/10.3102/0162373707299550
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