Background: Clustered randomized controlled trials are commonly used to evaluate the effectiveness of treatments. Frequently, stratified or paired designs are adopted in practice. Fogarty (2018) studied variance estimators for stratified and not clustered experiments and Schochet et. al. (2022) studied that for stratified, clustered RCTs with…

Random encouragement designs are randomized controlled trials (RCTs) that test interventions aimed at increasing participation in a program or activity whose take up is not universal. In these RCTs, instead of randomizing individuals or clusters directly into treatment and control groups to participate in a program or activity, the randomization…

Background: The data revolution in education has led to more data collection, more randomized controlled trials (RCTs), and more data collection within RCTs. Often following IES recommendations, researchers studying program effectiveness gather data on how the intervention was implemented. Educational implementation data can be complex, including…

Background: Randomized controlled trials (RCTs) give unbiased estimates of average effects. However, positive effects for the majority of students may mask harmful effects for smaller subgroups, and RCTs often have too small a sample to estimate these subgroup effects. In many RCTs, covariate and outcome data are drawn from a larger database. For…

Background: Power analysis and sample size planning are key components in designing cluster randomized trials (CRTs), a common study design to test treatment effect by randomizing clusters or groups of individuals. Sample size determination in two-level CRTs requires knowledge of more than one design parameter, such as the effect size and the…

Background: When RCTs are not feasible and time series data are available, panel data methods can be used to estimate treatment effects on outcomes, by exploiting variation in policies and conditions over time and across locations. A complication with these methods, however, is that treatment timing often varies across the sample, for example, due…

Background: Researchers are often interested in testing the effectiveness of an intervention on multiple outcomes, for multiple subgroups, at multiple points in time, or across multiple treatment groups. The resulting multiplicity of statistical hypothesis tests can lead to spurious findings of effects. Multiple testing procedures (MTPs)…

Design-based methods have recently been developed as a way to analyze data from impact evaluations of interventions, programs, and policies (Freedman, 2008; Lin, 2013; Imbens and Rubin, 2015; Schochet, 2013, 2016; Yang and Tsiatis, 2001). The non-parametric estimators are derived using the building blocks of experimental designs with minimal…

The purpose of this study is to propose a general framework for power analyses to detect the moderator effects in two- and three-level cluster randomized trials (CRTs). The study specifically aims to: (1) develop the statistical formulations for calculating statistical power, minimum detectable effect size (MDES) and its confidence interval to…

Cluster randomized trials (CRTs), or studies in which intact groups of individuals are randomly assigned to a condition, are becoming more common in evaluation studies of educational programs. A specific type of CRT in which clusters are randomly assigned to treatment within blocks or sites, known as multisite cluster randomized trials (MSCRTs),…

Randomized experiments are generally considered to provide the strongest basis for causal inferences about cause and effect. Consequently randomized field trials have been increasingly used to evaluate the effects of education interventions, products, and services. Populations of interest in education are often hierarchically structured (such as…

A common design in education research for interventions operating at a group or cluster level is a cluster randomized trial (CRT) (Bloom, 2005). In CRTs, intact clusters (e.g., schools) are assigned to treatment conditions rather than individuals (e.g., students) and are frequently an effective way to study interventions because they permit…

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…

For intervention studies involving binary treatment variables, procedures for power analysis have been worked out and computerized estimation tools are generally available. The purpose of this study is to: (1) develop the statistical formulations for calculating statistical power, minimum detectable effect size (MDES) and its confidence interval,…

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…