Estimating average treatment effects for clustered RCTs with recruitment bias.

In clustered randomized controlled trials (RCTs), sample recruitment is often conducted after cluster randomization. This timing can lead to recruitment bias if access to the intervention affects the composition of study-eligible cluster entrants and study consenters. This article develops a potential outcomes framework in such settings that yields a causal estimand that pertains to the always-recruited in either research condition.

The Complier Average Causal Effect Parameter for Multiarmed RCTs.

In randomized controlled trials, the complier average causal effect (CACE) parameter is often of policy interest because it pertains to intervention effects for study units that comply with their research assignments and receive a meaningful dose of treatment services. Causal inference methods for identifying and estimating the CACE parameter using an instrumental variables (IV) framework are well established for designs with a single treatment and control group. This article uses a parallel IV framework to discuss and build on the much smaller literature on estimation of CACE parameters for designs with multiple treatment groups.

An approach for addressing the multiple testing problem in social policy impact evaluations.

In social policy evaluations, the multiple testing problem occurs due to the many hypothesis tests that are typically conducted across multiple outcomes and subgroups, which can lead to spurious impact findings. This article discusses a framework for addressing this problem that balances Types I and II errors. The framework involves specifying confirmatory and exploratory analyses in study protocols, delineating confirmatory outcome domains, conducting t tests on composite domain outcomes, and applying multiplicity corrections to composites across domains to obtain summative impact evidence.

Using propensity scoring to estimate program-related subgroup impacts in experimental program evaluations.

This article discusses the use of propensity scoring in experimental program evaluations to estimate impacts for subgroups defined by program features and participants' program experiences. The authors discuss estimation issues and provide specification tests. They also discuss the use of an overlooked data collection design--obtaining predictions that program intake staff make about applicants' likely program assignments and experiences--that could improve the quality of matched comparison samples.

The effectiveness of early head start for 3-year-old children and their parents: lessons for policy and programs.

Early Head Start, a federal program begun in 1995 for low-income pregnant women and families with infants and toddlers, was evaluated through a randomized trial of 3,001 families in 17 programs. Interviews with primary caregivers, child assessments, and observations of parent-child interactions were completed when children were 3 years old. Caregivers were diverse in race-ethnicity, language, and other characteristics.