Data and Code for: Optimality of Matched-Pair Designs in Randomized Controlled Trials
Principal Investigator(s): View help for Principal Investigator(s) Yuehao Bai, University of Southern California
Version: View help for Version V2
| Name | File Type | Size | Last Modified |
|---|---|---|---|
| 01_simulation | 05/20/2024 04:27:PM | ||
| 02_analysis | 09/30/2022 10:37:AM |
Project Description
Summary:
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In randomized controlled trials (RCTs), treatment is often assigned by stratified randomization. I show that among all stratified randomization schemes which treat all units with probability one half, a certain matched-pair design achieves the maximum statistical precision for estimating the average treatment effect (ATE). In an important special case, the optimal design pairs units according to the baseline outcome. In a simulation study based on datasets from 10 RCTs, this design lowers the standard error for the estimator of the ATE by 10% on average, and by up to 34%, relative to the original designs.
Scope of Project
JEL Classification:
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C12 Hypothesis Testing: General
C13 Estimation: General
C14 Semiparametric and Nonparametric Methods: General
C90 Design of Experiments: General
C12 Hypothesis Testing: General
C13 Estimation: General
C14 Semiparametric and Nonparametric Methods: General
C90 Design of Experiments: General
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