A Primer on the Analysis of Randomized Experiments and a Survey of some Recent Advances

TL;DR

This paper reviews recent advances in the analysis of randomized experiments, highlighting subtle aspects like stratification, regression adjustment, and cluster randomization that improve understanding and interpretation.

Contribution

It provides a comprehensive overview of new methodological developments in analyzing randomized experiments, emphasizing practical insights and recent research findings.

Findings

Enhanced understanding of stratification effects

Insights into regression adjustment benefits

Improved methods for cluster randomization analysis

Abstract

The past two decades have witnessed a surge of new research in the analysis of randomized experiments. The emergence of this literature may seem surprising given the widespread use and long history of experiments as the "gold standard" in program evaluation, but this body of work has revealed many subtle aspects of randomized experiments that may have been previously unappreciated. This article provides an overview of some of these topics, primarily focused on stratification, regression adjustment, and cluster randomization.