Ideally, nonexperimental methods that aim to replicate the results of rigorous randomized experiments focus on the intent to treat (ITT) experimental impact estimate, the most causally rigorous measure. This working paper develops a new replication approach that facilitates testing...

Statistical procedures that correct for multiple testing typically result in hypothesis tests with reduced statistical power because adjustment methods reduce the likelihood of identifying real differences between contrasted groups. There is disagreement among researchers about the use of...

Randomized control trials (RCTs) in the education field typically examine the intention-to-treat parameter, which is estimated by comparing the mean outcomes of treatment group members to those of the control group. This report examines the identification and estimation of the complier average...

Variation in treatment effects has important implications for education practice—and for facilitating the most efficient use of limited resources—by informing decisions about how best to target interventions and how to improve the design or implementation of interventions....

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...

To improve precision of estimated treatment effects, education randomized control trials (RCTs) often use pretest–post-test experimental designs. For logistical reasons, however, pretest data often are collected after random assignment, so including them in the analysis could bias post-test...

Presents estimates of the impacts of Job Corps on participants' employment and related outcomes during the 48 months after random assignment.