Statistical Power for School-Based RCTs with Binary Outcomes
AbstractThis article develops a new approach for calculating appropriate sample sizes for school-based randomized controlled trials (RCTs) with binary outcomes using logit models with and without baseline covariates. The theoretical analysis develops sample size formulas for clustered designs in which random assignment is at the school or teacher level using generalized estimating equation methods. The key finding is that sample sizes of 40 to 60 schools that are typically included in clustered RCTs for student test score or behavioral scale outcomes will often be insufficient for binary outcomes.
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Bibliographic InfoPaper provided by Mathematica Policy Research in its series Mathematica Policy Research Reports with number 7874.
Date of creation: 30 Jun 2013
Date of revision:
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Statistical Power; Binary Outcomes; Clustered Designs; Randomized Control Trials;
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- I - Health, Education, and Welfare
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