This article examines the estimation of two-stage clustered designs for education randomized control trials (RCTs) using the nonparametric Neyman causal inference framework that underlies experiments. The key distinction between the considered causal models is whether potential treatment and...

For randomized controlled trials (RCTs) of education interventions, estimates of associations between student and mediating teacher practice outcomes can help examine the extent to which the data support the study's conceptual model. They can also identify mediators most associated with student...

For randomized controlled trials (RCTs) of education interventions, estimates of associations between student and mediating teacher practice outcomes can help examine the extent to which the data support the study's conceptual model. They can also identify mediators most associated with student...

In randomized control trials (RCTs) in the education field, the complier average causal effect (CACE) parameter is often of policy interest, because it pertains to intervention effects for students who receive a meaningful dose of treatment services. This article uses a causal inference and...