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Balancing tests in stratified randomized controlled trials: A cautionary note

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  • Firpo, Sergio
  • Foguel, Miguel N.
  • Jales, Hugo

Abstract

We study the properties of imbalances tests of predetermined characteristics (covariates) in stratified randomized controlled trials. When the parameter of interest is a weighted average of the causal effects at all strata, then a test statistic based on a fixed effects regression model may suffice to detect the relevant imbalances. This will be true under a condition on the partial correlation between covariates and the outcome variable (uniformity condition). If that condition is violated, then the test based on the fixed effects regression will lack power. In that case, a test based on the fully saturated regression model can overcome this problem. Finally, we provide an omnibus test for the relevance of controlling for the covariates when estimating the average treatment effect (ATE).

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  • Firpo, Sergio & Foguel, Miguel N. & Jales, Hugo, 2020. "Balancing tests in stratified randomized controlled trials: A cautionary note," Economics Letters, Elsevier, vol. 186(C).
    • Handle: RePEc:eee:ecolet:v:186:y:2020:i:c:s0165176519303878
    DOI: 10.1016/j.econlet.2019.108771
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    References listed on IDEAS

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    Cited by:

    1. Piza, Caio & Zwager, Astrid & Ruzzante, Matteo & Dantas, Rafael & Loureiro, Andre, 2024. "Teacher-led innovations to improve education outcomes: Experimental evidence from Brazil," Journal of Public Economics, Elsevier, vol. 234(C).
    2. Brandon Genetin & Joyce Chen & Vladimir Kogan & Alan Kalish, 2022. "Mitigating implicit bias in student evaluations: A randomized intervention," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 44(1), pages 110-128, March.

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