Statistical Power for School-Based RCTs with Binary Outcomes.

This 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.