In recent years, the regression discontinuity design (RDD) has gained widespread recognition as a quasi-experimental method that when used correctly, can produce internally valid estimates of causal effects of a treatment, a program or an intervention (hereafter referred to as treatment effects). In an RDD study, subjects or groups of subjects…

The regression discontinuity design (RDD) has the potential to yield findings with causal validity approaching that of the randomized controlled trial (RCT). However, Schochet (2008a) estimated that, on average, an RDD study of an education intervention would need to include three to four times as many schools or students as an RCT to produce…

In school-based randomized control trials (RCTs), a common design is to follow student cohorts over time. For such designs, education researchers usually focus on the place-based (PB) impact parameter, which is estimated using data collected on all students enrolled in the study schools at each data collection point. A potential problem with this…

Randomized trials of educational interventions often face logistical hurdles (Cook, 2002). For example, sometimes they are prevented from reaching their full-term. This would happen if, as a condition of participation, subjects insist on receiving the treatment program within a certain timeframe. This timeframe may be shorter than the full-term…

This paper provides practical guidance for researchers who are designing and analyzing studies that randomize schools--which comprise three levels of clustering (students in classrooms in schools)--to measure intervention effects on student academic outcomes when information on the middle level (classrooms) is missing. This situation arises…