Estimating the average treatment effect in randomized experiments with missing covariates. Time for a New Angle!': Unravel the Mystery of Split-Plot Designs via the Potential Outcomes Prism.

Anqi Zhao is an Assistant Professor in the Decision Sciences area. Her research interests are experimental design, causal inference, survey sampling, and missing data, with applications to social, biomedical, and business sciences.

Journal Article Biometrika · December 1, 2024 Covariate adjustment can improve precision in analysing randomized experiments. With fully observed data, regression adjustment and propensity score weighting are asymptotically equivalent in improving efficiency over unadjusted analysis. When some outcome ... Full text Cite.

2023年11月17日 · View a PDF of the paper titled Covariate adjustment in randomized experiments with missing outcomes and covariates, by Anqi Zhao and Peng Ding and Fan Li

Zhao, A. and Ding, P. (2022). Regression-based causal inference with factorial experiments: estimands, model specifications and design-based properties . Biometrika , 109, 799--815 .

Anqi Zhao. Unknown affiliation. Verified email at princeton.edu. Articles Cited by Public access. Title. Sort. Sort by citations Sort by year Sort by title. Cited by. Cited by. ... R Le, Y Huang, A Zhao, S Gao. Journal of Genetics and Genomics 47 (3), 123-130, 2020. 11: 2020: The system can't perform the operation now. Try again later. Articles ...

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Estimating the Average Treatment Effect in Randomized Experiments with Missing Covariates Journal of the American Statistical Association 119, no. 545 (January 1, 2024): 450–60. …