In multisite trials, learning about treatment effect variation across sites is critical for understanding where and for whom a program works. Unadjusted comparisons, however, capture "compositional" differences in the distributions of unit-level features as well as "contextual" differences in site-level features, including…

In multisite trials, learning about treatment effect variation across sites is critical for understanding where and for whom a program works. Unadjusted comparisons, however, capture "compositional" differences in the distributions of unit-level features as well as "contextual" differences in site-level features, including…

Among econometricians, instrumental variable (IV) estimation is a commonly used technique to estimate the causal effect of a particular variable on a specified outcome. However, among applied researchers in the social sciences, IV estimation may not be well understood. Although there are several IV estimation primers from different fields, most…

In basic regression discontinuity (RD) designs, causal inference is limited to the local area near a single cutoff. To strengthen the generality of the RD treatment estimate, a design with multiple cutoffs along the assignment variable continuum can be applied. The availability of multiple cutoffs allows estimation of a pooled average treatment…

In basic regression discontinuity (RD) designs, causal inference is limited to the local area near a single cutoff. To strengthen the generality of the RD treatment estimate, a design with multiple cutoffs along the assignment variable continuum can be applied. The availability of multiple cutoffs allows estimation of a pooled average treatment…

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…

Design-based methods have recently been developed as a way to analyze data from impact evaluations of interventions, programs, and policies. The impact estimators are derived using the building blocks of experimental designs with minimal assumptions, and have good statistical properties. The methods apply to randomized controlled trials (RCTs) and…

A new design-based theory has recently been developed to estimate impacts for randomized controlled trials (RCTs) and basic quasi-experimental designs (QEDs) for a wide range of designs used in social policy research (Imbens & Rubin, 2015; Schochet, 2016). These methods use the potential outcomes framework and known features of study designs…

Design-based methods have recently been developed as a way to analyze data from impact evaluations of interventions, programs, and policies (Imbens and Rubin, 2015; Schochet, 2015, 2016). The estimators are derived using the building blocks of experimental designs with minimal assumptions, and are unbiased and normally distributed in large samples…

Cluster randomized trials (CRTs), or studies in which intact groups of individuals are randomly assigned to a condition, are becoming more common in the evaluation of educational programs, policies, and practices. The website for the National Center for Education Evaluation and Regional Assistance (NCEE) reveals they have launched over 30…

Objective: The purpose of this study was to document the development and testing costs of the Enhanced Alcohol Risk Management (eARM) intervention, a web enhanced training program to prevent alcohol sales to intoxicated bar patrons and to estimate its implementation costs in a "real world", non-research setting. Methods: Data for this…

To date, evaluation research and policy analysis have focused mainly on average program impacts and paid little systematic attention to their variation. Recently, the growing number of multi-site randomized trials that are being planned and conducted make it increasingly feasible to study "cross-site" variation in impacts. Important…