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Optimality of Matched-Pair Designs in Randomized Controlled Trials

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  • Yuehao Bai

Abstract

In randomized controlled trials, treatment is often assigned by stratified randomization. I show that among all stratified randomization 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.

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  • Yuehao Bai, 2022. "Optimality of Matched-Pair Designs in Randomized Controlled Trials," American Economic Review, American Economic Association, vol. 112(12), pages 3911-3940, December.
    • Handle: RePEc:aea:aecrev:v:112:y:2022:i:12:p:3911-40
    DOI: 10.1257/aer.20201856
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    1. Suresh de Mel & David McKenzie & Christopher Woodruff, 2019. "Labor Drops: Experimental Evidence on the Return to Additional Labor in Microenterprises," American Economic Journal: Applied Economics, American Economic Association, vol. 11(1), pages 202-235, January.
    2. Erika Deserranno & Miri Stryjan & Munshi Sulaiman, 2019. "Leader Selection and Service Delivery in Community Groups: Experimental Evidence from Uganda," American Economic Journal: Applied Economics, American Economic Association, vol. 11(4), pages 240-267, October.
    3. Alan Gerber & Mitchell Hoffman & John Morgan & Collin Raymond, 2020. "One in a Million: Field Experiments on Perceived Closeness of the Election and Voter Turnout," American Economic Journal: Applied Economics, American Economic Association, vol. 12(3), pages 287-325, July.
    4. Jean N. Lee & Jonathan Morduch & Saravana Ravindran & Abu Shonchoy & Hassan Zaman, 2021. "Poverty and Migration in the Digital Age: Experimental Evidence on Mobile Banking in Bangladesh," American Economic Journal: Applied Economics, American Economic Association, vol. 13(1), pages 38-71, January.
    5. Max Tabord-Meehan, 2023. "Stratification Trees for Adaptive Randomisation in Randomised Controlled Trials," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(5), pages 2646-2673.
    6. Martin Abel & Rulof Burger & Patrizio Piraino, 2020. "The Value of Reference Letters: Experimental Evidence from South Africa," American Economic Journal: Applied Economics, American Economic Association, vol. 12(3), pages 40-71, July.
    7. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881, January.
    8. Jeanne Lafortune & Julio Riutort & José Tessada, 2018. "Role Models or Individual Consulting: The Impact of Personalizing Micro-entrepreneurship Training," American Economic Journal: Applied Economics, American Economic Association, vol. 10(4), pages 222-245, October.
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    Cited by:

    1. Bai, Yuehao & Liu, Jizhou & Shaikh, Azeem M. & Tabord-Meehan, Max, 2024. "Inference in cluster randomized trials with matched pairs," Journal of Econometrics, Elsevier, vol. 245(1).
    2. Yuehao Bai & Azeem M. Shaikh & Max Tabord-Meehan, 2024. "A Primer on the Analysis of Randomized Experiments and a Survey of some Recent Advances," Papers 2405.03910, arXiv.org.
    3. Yuehao Bai & Meng Hsuan Hsieh & Jizhou Liu & Max Tabord-Meehan, 2022. "Revisiting the Analysis of Matched-Pair and Stratified Experiments in the Presence of Attrition," Papers 2209.11840, arXiv.org, revised Oct 2023.
    4. Jiang, Liang & Phillips, Peter C.B. & Tao, Yubo & Zhang, Yichong, 2023. "Regression-adjusted estimation of quantile treatment effects under covariate-adaptive randomizations," Journal of Econometrics, Elsevier, vol. 234(2), pages 758-776.
    5. Laurent Davezies & Guillaume Hollard & Pedro Vergara Merino, 2024. "Revisiting Randomization with the Cube Method," Papers 2407.13613, arXiv.org.
    6. Jinglong Zhao, 2023. "Adaptive Neyman Allocation," Papers 2309.08808, arXiv.org, revised Sep 2023.
    7. Yuehao Bai & Jizhou Liu & Azeem M. Shaikh & Max Tabord-Meehan, 2023. "On the Efficiency of Finely Stratified Experiments," Papers 2307.15181, arXiv.org, revised Feb 2025.
    8. Cai, Yong & Rafi, Ahnaf, 2024. "On the performance of the Neyman Allocation with small pilots," Journal of Econometrics, Elsevier, vol. 242(1).
    9. Guillermo Cruces & Dario Tortarolo & Gonzalo Vazquez-Bare, 2022. "Design of two-stage experiments with an application to spillovers in tax compliance," IFS Working Papers W22/32, Institute for Fiscal Studies.
    10. Jizhou Liu, 2023. "Inference for Two-stage Experiments under Covariate-Adaptive Randomization," Papers 2301.09016, arXiv.org, revised Oct 2024.
    11. Bugni, Federico A. & Gao, Mengsi, 2023. "Inference under covariate-adaptive randomization with imperfect compliance," Journal of Econometrics, Elsevier, vol. 237(1).
    12. Yuehao Bai & Meng Hsuan Hsieh & Jizhou Liu & Max Tabord‐Meehan, 2024. "Revisiting the analysis of matched‐pair and stratified experiments in the presence of attrition," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 256-268, March.
    13. Max Cytrynbaum, 2024. "Finely Stratified Rerandomization Designs," Papers 2407.03279, arXiv.org, revised Jan 2025.
    14. Jinglong Zhao, 2024. "Experimental Design For Causal Inference Through An Optimization Lens," Papers 2408.09607, arXiv.org, revised Aug 2024.
    15. Yuehao Bai & Jizhou Liu & Max Tabord-Meehan, 2022. "Inference for Matched Tuples and Fully Blocked Factorial Designs," Papers 2206.04157, arXiv.org, revised Nov 2023.

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    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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