Optimality of Matched-Pair Designs in Randomized Controlled Trials

In randomized controlled trials, treatment is often assigned by strat-ified randomization. I show that among all stratified randomiza-tion schemes that treat all units with probability one half, a certain matched-pair design achieves the maximum statistical precision for estimating the average treatment effect. In an important special case, the optimal design pairs units according to the baseline outcome. In a simulation study based on datasets from ten randomized controlled trials, this design lowers the standard error for the estimator of the average treatment effect by 10 percent on average, and by up to 34 percent, relative to the original designs. (JEL C13, C21)

Automated summary

This article examines the application of stratified randomization in randomized controlled trials and finds that a certain matched-pair design achieves the highest statistical precision for estimating the average treatment effect. In certain special cases, pairing units based on the baseline outcome can lead to optimal results.