Statistical Power for Regression Discontinuity Designs in Education Empirical Estimates of Design Effects Relative to Randomized Controlled Trials

John Deke and Lisa Dragoset

Mathematica Policy Research Reports from Mathematica Policy Research

Abstract: Using data from four previously published education studies, this working paper finds that a study using a regression discontinuity design needs between 9 and 17 times as many schools or students as a randomized controlled trial to produce an impact with the same level of statistical precision. The need for a large sample is driven primarily by bandwidth selection, not adjusting for random misspecification error.

Keywords: Statistical; Power; Regression; Discontinuity; Designs; Randomized; Controlled; Trials; Education (search for similar items in EconPapers)
JEL-codes: I (search for similar items in EconPapers)
Date: 2012-06-30
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