Corpus ID: 236772813

To adjust or not to adjust? Estimating the average treatment effect in randomized experiments with missing covariates

@inproceedings{Zhao2021ToAO,
  title={To adjust or not to adjust? Estimating the average treatment effect in randomized experiments with missing covariates},
  author={Anqi Zhao and Peng Ding},
  year={2021}
}
Complete randomization allows for consistent estimation of the average treatment effect based on the difference in means of the outcomes without strong modeling assumptions on the outcome-generating process. Appropriate use of the pretreatment covariates can further improve the estimation efficiency. However, missingness in covariates is common in experiments and raises an important question: should we adjust for covariates subject to missingness, and if so, how? The unadjusted difference in… Expand

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