Estimating treatment effects for subgroups defined by posttreatment behavior (i.e., estimating causal effects in a principal stratification framework) can be technically challenging and heavily reliant on strong assumptions. We investigate an alternative path: using bounds to identify ranges of possible effects that are consistent with the data.…

Recent literature has underscored the critical role of treatment effect variation in estimating and understanding causal effects. This approach, however, is in contrast to much of the foundational research on causal inference. Linear models, for example, classically rely on constant treatment effect assumptions, or treatment effects defined by…

Increasingly, researchers are interested in questions regarding treatment-effect variation across partially or fully latent subgroups defined not by pretreatment characteristics but by postrandomization actions. One promising approach to address such questions is principal stratification. Under this framework, a researcher defines endogenous…

Modeling the distribution of site level effects is an important problem, but it is also an incredibly difficult one. Current methods rely on distributional assumptions in multilevel models for estimation. There it is hoped that the partial pooling of site level estimates with overall estimates, designed to take into account individual variation as…

The goal of this study is to better understand how methods for estimating treatment effects of latent groups operate. In particular, the authors identify where violations of assumptions can lead to biased estimates, and explore how covariates can be critical in the estimation process. For each set of approaches, the authors first review the…

While the adjusted cohort graduation rate of students in the United States has reached 80 percent during the 2011-12 school year (Stetser & Stillwell, 2014), in the School District of Philadelphia (SDP) only 57% of its students graduate from high school in four years, which is typical of large urban school districts (Swanson, 2009). Moreover,…

Head Start programs currently provide early childhood education and family support services to more than 900,000 low-income children and their families across the United States with an annual budget of around $8 billion in state and federal funds. Researchers and policy makers have debated the program's effectiveness since its inception in 1964.…

This study seeks to answer the following question: Are impacts on Head Start classroom quality associated with impacts of Head Start on children's learning and development? This study employs a variety of descriptive and quasi-experimental methods to explore the role of classroom quality as a mediator or mechanism of Head Start impacts. This…