CV

Office hour: Thursday 10:00–11:30

Contact

Email: mwfy(at)pku.edu.cn

Presentations

Teaching

Research interest

My research interest centers around

and their application.

Publications

Peer-reviewed papers

Miao W., Ding P., and Geng Z. (2016). Identifiability of normal and normal mixture models with nonignorable missing data. Journal of the American Statistical Association, 111:1673–1683.

Miao W. and Tchetgen Tchetgen E. (2016). On varieties of doubly robust estimators under missingness not at random with a shadow variable. Biometrika, 103:475–482.

Miao W. and Tchetgen Tchetgen E. (2017). Bias attenuation and identification of causal effects with multiple negative controls. American Journal of Epidemiology, 185:950–953.

Miao W., Geng Z., and Tchetgen Tchetgen E. (2018). Identifying causal effects with proxy variables of an unmeasured confounder. Biometrika, 105:987–993

Miao W. and Tchetgen Tchetgen E. (2018). Identification and inference with non-ignorable missing covariate data. Statistica Sinica, 28:2049–2067.

Sun B. L., Liu L., Miao W., Wirth K., Robins J. M., and Tchetgen Tchetgen E. (2018). Semiparametric estimation with data missing not at random using an instrumental variable. Statistica Sinica, 28:1965–1983.

苗旺,刘春晨,耿直 (2018). 因果推断的统计方法. 《中国科学·数学》, 48:1753–1778.

Geng Z., Liu Y., Liu C. C., and Miao W. (2019). Evaluation of causal effects and local structure learning of causal networks. Annual Review of Statistics and Its Application, 6:103–124.

Shi X., Miao W., Nelson J., and Tchetgen Tchetgen E. (2020). Multiply robust causal inference with double-negative control adjustment for categorical unmeasured confounding. Journal of the Royal Statistical Society: Series B, 82:521–540.

Liu L., Miao W., Sun B. L., Robins J. M., and Tchetgen Tchetgen E. (2020). Identification and inference for marginal average treatment effect on the treated with an instrumental variable. Statistica Sinica, 30:1517–1541.

Kuang, K., Li, L., Geng, Z., Xu, L., Zhang, K., Liao, BS., Huang HX., Ding P., Miao W., and Jiang, Z. (2020). Causal Inference. Engineering, 6:253–263.

Li H., Miao W., Cai Z., Liu X., Zhang T., Xue F., and Geng Z (2020). Causal data fusion methods using summary-level statistics for a continuous outcome. Statistics in Medicine, 39:1054–1067.

Shi X., Miao W., and Tchetgen Tchetgen E. (2020). A Selective Review of Negative Control Methods in Epidemiology. Current Epidemiology Reports, 7:190–202.

Sun BL. and Miao W. (2020). On Semiparametric Instrumental Variable Estimation of Average Treatment Effects through Data Fusion. Statistica Sinica, in presss arXiv

Miao W., Li W., Hu WJ., Wang RY., and Geng Z. (2021). Invited Commentary: Estimation and Bounds Under Data Fusion. American Journal of Epidemiology, in press.

Li XY., Miao W., Lu F., and Zhou XH. (2021). Improving efficiency of inference in randomized trials with external controls. Biometrics, in press. arXiv \(\color{blue}{\text{Winner of the Best Paper Award on the 2021 National Annual Biostatistics Conference.}}\)

Unpublished manuscripts

Miao W., Liu L., Tchetgen Tchetgen E., and Geng Z. Identification and doubly robust estimation of data missing not at random with a shadow variable. arXiv

Miao W., Shi X., and Tchetgen Tchetgen E. A confounding bridge approach for double negative control inference on causal effects. arXiv

Miao W., Hu WJ., Ogburn E. L., and Zhou XH. Identifying Effects of Multiple Causes With an Unobserved Confounder. arXiv; Codes

Tchetgen Tchetgen E., Ying A., Cui YF., Shi X., and Miao W. An Introduction to Proximal Causal Learning. arXiv

Cui YF., Pu HM., Shi X., Miao W., and Tchetgen Tchetgen E. Semiparametric proximal causal inference. arXiv

Wang, RY., Wang, QH., Miao, W., and Zhou, XH. Sharp bounds for variance of treatment effect estimators in the finite population in the presence of covariates. arXiv

Grants

北京市自然科学基金重点项目 2019–2023 人工智能的统计理论与算法基础

智源人工智能研究院项目 2019–2021 过参数化模型与因果学习的统计理论

国家自然科学基金面上项目 2021–2024 关于无对照研究和中介分析的因果建模与推断

Students

Xinyu Li (PhD), Yilin Li (PhD), Yujing Gao (Master)