Cluster-randomized trials have been widely used to evaluate the treatment effects of interventions on student outcomes. When interventions are implemented by teachers, researchers need to account for the nested structure in schools (i.e., students are nested within teachers nested within schools). Schools usually have a very limited number of…

Random encouragement designs evaluate treatments that aim to increase participation in a program or activity. These randomized controlled trials (RCTs) can also assess the mediated effects of participation itself on longer term outcomes using a complier average causal effect (CACE) estimation framework. This article considers power analysis…

Background: Education scientists are increasingly interested in constructing interventions that are adaptive over time to suit the evolving needs of students, classrooms, or schools. Such "adaptive interventions" (also referred to as dynamic treatment regimens or dynamic instructional regimes) determine which treatment should be offered…

Random encouragement designs are randomized controlled trials (RCTs) that test interventions aimed at increasing participation in a program or activity whose take up is not universal. In these RCTs, instead of randomizing individuals or clusters directly into treatment and control groups to participate in a program or activity, the randomization…

Evaluators of education interventions are increasingly designing studies to detect impacts much smaller than the 0.20 standard deviations that Cohen characterized as "small." While the need to detect smaller impacts is based on compelling arguments that such impacts are substantively meaningful, the drive to detect smaller impacts may…

Ainsworth et al.'s paper "Sources of Bias in Outcome Assessment in Randomised Controlled Trials: A Case Study" examines alternative accounts for a large difference in effect size between 2 outcomes in the same intervention evaluation. It argues that the probable explanation relates to masking: Only one outcome measure was administered by…

This article assesses the likely generalizability of educational treatment-effect estimates from regression discontinuity designs (RDDs) when treatment assignment is based on academic pretest scores. Our assessment uses data on outcome and pretest measures from six educational experiments, ranging from preschool through high school, to estimate…

This article assesses the likely generalizability of educational treatment-effect estimates from regression discontinuity designs (RDDs) when treatment assignment is based on academic pretest scores. Our assessment uses data on outcome and pretest measures from six educational experiments, ranging from preschool through high school, to estimate…

Evaluators of education interventions are increasingly designing studies to detect impacts much smaller than the 0.20 standard deviations that Cohen (1988) characterized as "small." While the need to detect smaller impacts is based on compelling arguments that such impacts are substantively meaningful, the drive to detect smaller impacts…

The increasing availability of data from multi-site randomized trials provides a potential opportunity to use instrumental variables methods to study the effects of multiple hypothesized mediators of the effect of a treatment. We derive nine assumptions needed to identify the effects of multiple mediators when using site-by-treatment interactions…

Randomized controlled trials (RCTs) and regression discontinuity (RD) studies both provide estimates of causal effects. A major difference between the two is that RD only estimates local average treatment effects (LATE) near the cutoff point of the forcing variable. This has been cited as a drawback to RD designs (Cook & Wong, 2008).…