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The Cost of Imbalance in Clinical Trials

Author

Listed:
  • Sylvain Chassang

    (Princeton University)

  • Rong Feng

    (New York University)

Abstract

Clinical trials following the "gold standard" of random assignment frequently use independent lotteries to allocate patients to treatment and control arms. Unfortunately, independent assignment can generate treatment and control arms that are unbalanced (i.e. treatment and control populations with significantly different demographics). This is regrettable since other assignment methods such as matched pair designs ensure balance across arms while maintaining randomization and permitting inference. This paper seeks to measure the cost of imbalance with respect to gender in a sample of roughly 2000 clinical studies. We document significant imbalance: 25% of experiments have at least 26% more men in one treatment arm than in the other. In addition, clinical trials with greater imbalance have more dispersed treatment effects, indicating that imbalance reduces the informativeness of experiments. A simple structural model suggests that for a typical experiment, using a balanced random design could deliver informativeness gains equivalent to increasing the sample size by 18%.

Suggested Citation

  • Sylvain Chassang & Rong Feng, 2020. "The Cost of Imbalance in Clinical Trials," Working Papers 2020-12, Princeton University. Economics Department..
  • Handle: RePEc:pri:econom:2020-12
    as

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    File URL: https://www.sylvainchassang.org/assets/papers/trial_balance.pdf
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    References listed on IDEAS

    as
    1. Kari Lock Morgan & Donald B. Rubin, 2015. "Rerandomization to Balance Tiers of Covariates," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1412-1421, December.
    2. Miriam Bruhn & David McKenzie, 2009. "In Pursuit of Balance: Randomization in Practice in Development Field Experiments," American Economic Journal: Applied Economics, American Economic Association, vol. 1(4), pages 200-232, October.
    3. Abhijit V. Banerjee & Sylvain Chassang & Sergio Montero & Erik Snowberg, 2020. "A Theory of Experimenters: Robustness, Randomization, and Balance," American Economic Review, American Economic Association, vol. 110(4), pages 1206-1230, April.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    clinical trials; balance; gender; informativeness;
    All these keywords.

    JEL classification:

    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality

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