Email: mwfy(at)pku.edu.cn
2023 Spring 概率统计 (B) (00132380)
2022 Fall 高等统计学 Advanced Theory of Statistics (00112640)
2022 Spring 半参数模型 Semiparametric Model (00112880)
因果推断，观察性研究和 2021 年诺贝尔经济学奖 (Causal inference, observational studies, and the 2021 Nobel Prize in economics)
2021 Spring 高等统计选讲I Selected Topics on Advanced Statistics I (00112230)
2020 Fall R语言与数据可视化 Data analysis and graphics with R (02812710)
2020 Spring 概率统计 Probability and Statistics (02834720)
2019 Fall R语言与数据可视化 Data analysis and graphics with R (02812710)
2019 Spring 概率统计 Probability and Statistics (02834720)
2018 Fall 统计文化和实践 Statistical culture and practice (02839050)
PhD students: Xinyu Li, Yilin Li, Ping Zhang, Naiwen Ying
Master students: Peiyu He, Yujing Gao
Miao, W., P. Ding, and Z. Geng (2016). Identifiability of normal and normal mixture models with nonignorable missing data. Journal of the American Statistical Association 111, 1673–1683 Winner of the Zhongjiaqing Best Paper Award (to Miao) given by Chinese Society of Probability and Statistics.
Miao, W. and E. Tchetgen Tchetgen (2016). On varieties of doubly robust estimators under missingness not at random with a shadow variable. Biometrika 103, 475–482
Miao, W. and E. Tchetgen Tchetgen (2017). Invited commentary: Bias attenuation and identification of causal effects with multiple negative controls. American Journal of Epidemiology 185, 950–953
Miao, W., Z. Geng, and E. Tchetgen Tchetgen (2018). Identifying causal effects with proxy variables of an unmeasured confounder. Biometrika 105, 987–993
Miao, W. and E. Tchetgen Tchetgen (2018). Identification and inference with nonignorable missing covariate data. Statistica Sinica 28, 2049–2067
Sun, B., L. Liu, W. Miao, K. Wirth, J. Robins, and E. Tchetgen Tchetgen (2018). Semiparametric estimation with data missing not at random using an instrumental variable. Statistica Sinica 28, 1965–1983
苗旺, 刘春辰, 耿直 (2018). 因果推断的统计方法. 中国科学: 数学 48, 1753–1778
Geng, Z., Y. Liu, C. Liu, and W. Miao (2019). Evaluation of causal effects and local structure learning of causal networks. Annual Review of Statistics and Its Application 6, 103–124
Liu, L., W. Miao, B. Sun, J. Robins, and E. Tchetgen Tchetgen (2020). Identification and inference for marginal average treatment effect on the treated with an instrumental variable. Statistica Sinica 30, 1517–1541
Kuang, K., L. Li, Z. Geng, L. Xu, K. Zhang, B. Liao, H. Huang, P. Ding, W. Miao, and Z. Jiang (2020). Causal inference. Engineering 6, 253–263
Shi, X., W. Miao, J. C. Nelson, and E. Tchetgen Tchetgen (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
Li, H., W. Miao, Z. Cai, X. Liu, T. Zhang, F. Xue, and Z. Geng (2020). Causal data fusion methods using summary-level statistics for a continuous outcome. Statistics in Medicine 39, 1054–1067
Shi, X., W. Miao, and E. Tchetgen Tchetgen (2020). A selective review of negative control methods in epidemiology. Current Epidemiology Reports 7, 190–202
Miao, W., W. Li, W. Hu, R. Wang, and Z. Geng (2021). Invited commentary: Estimation and bounds under data fusion. American Journal of Epidemiology, in press
Li, X., W. Miao, F. Lu, and X.-H. Zhou (2021). Improving efficiency of inference in clinical trials with external control data. Biometrics, in press arXiv Winner of the Best Paper Award (to Li) on the 2021 National Annual Biostatistics Conference.
Miao, W., W. Hu, E. L. Ogburn, and X. Zhou (2021). Identifying effects of multiple treatments in the presence of unmeasured confounding. Journal of the American Statistical Association, in press arXiv; Supplement; Codes
Tchetgen Tchetgen, E., O. Dukes, X. Shi, W. Miao, and D. Richardson (2022). Errors-in-variables bias in synthetic controls: a cautionary note and a potential solution. American Joural of Epidemiology, in press
Sun, B. and W. Miao (2022). On semiparametric instrumental variable estimation of average treatment effects through data fusion. Statistica Sinica 32, 569–590 arXiv
Shi, X., Z. Pan, and W. Miao (2022). Data integration in causal inference. WIREs Computational Statistics, in press. arXiv
Ying, A., W. Miao, X. Shi, and E. Tchetgen Tchetgen (2022). Proximal causal inference for complex longitudinal studies. Journal of the Royal Statistical Society: Series B, in press. arXiv Winner of the David P. Byar Award (to Ying) in Biometrics Section on JSM2022.
Wang, R., Q. Wang, and W. Miao (2022). A robust fusion-extraction procedure with summary statistics in the presence of biased sources. Biometrika, in press arXiv
Wang, R., Q. Wang, W. Miao, and X. Zhou (2022). Sharp bounds for variance of treatment effect estimators in the finite population in the presence of covariates. Statistica Sinica, in press. arXiv
苗旺，耿直 (2023). 因果推断，观察性研究和 2021 年诺贝尔经济学奖. 系统科学第三卷.
英乃文，苗旺，耿直 (2022). 因果作用评价与因果关系发现. 军事运筹与评估.
Zhang, J., W. Li, W. Miao, E. Tchetgen Tchetgen (2023). Proximal Causal Inference without Uniqueness Assumptions. Statistics and Probability Letters, in press.
Cui, Y., H. Pu, X. Shi, W. Miao, and E. Tchetgen Tchetgen (2023). Semiparametric proximal causal inference. Journal of the American Statistical Association, in press. arXiv
Miao, W., L. Liu, Y. Li, E. Tchetgen Tchetgen, and Z. Geng (2023). Identification and semiparametric efficiency theory of nonignorable missing data with a shadow variable. ACM/IMS Journal of Data Science, in press. arXiv
Li, K. Q., X. Shi, W. Miao, and E. Tchetgen Tchetgen (2023). Double negative control inference in test-negative design studies of vaccine effectiveness. Journal of the American Statistical Association, in press. arXiv
Li, W., W. Miao, and E. Tchetgen Tchetgen (2023). Identification and estimation of nonignorable missing outcome mean without identifying the full data distribution. Journal of the Royal Statistical Society: Series B, in press. arXiv
Li, YL., W. Miao, I. Shpitser, and E. Tchetgen Tchetgen (2023). A self-censoring model for multivariate nonignorable nonmonotone missing data. Biometrics, in press. arXiv
Tchetgen Tchetgen, E., A. Ying, Y. Cui, X. Shi, and W. Miao (2023). An introduction to proximal causal learning. Statistical Science, in press. arXiv
Shi, X., W. Miao, M. Hu, and E. Tchetgen Tchetgen (2022). Theory for identification and Inference with Synthetic Controls: A Proximal Causal Inference Framework. Revision invited by Journal of the American Statistical Association. arXiv
Miao, W., X. Li, and B. Sun (2022). A stableness of resistance model for nonresponse adjustment with callback. Revision invited by Journal of the Royal Statistical Society: Series B. arXiv; Slides 该论文在第六届全国统计学博士研究生学术论坛获一等奖，李新宇获奖.
Hu, W., R. Wang, W. Li, and W. Miao (2023). Paradoxes and resolutions for semiparametric fusion of individual and summary data. Revision invited by Biometrika. arXiv
Luo, S., W. Li, W. Miao, and Y. He (2022). Identification and estimation of causal effects in the presence of confounded principal strata arXiv
Miao, W., X. Shi, and E. Tchetgen Tchetgen (2018). A confounding bridge approach for double negative control inference on causal effects arXiv
Li, X., K. Li, X. Shi, BL. Sun and W. Miao (2023). Correction for nonignorable nonresponse bias in turnout estimation using callback data
He, P., Y. Li, and W. Miao (2023). Identification and estimation of causal effects with synthetic controls in the presence of interference
Zhang, P., R. Wang, and W. Miao (2023). Causal attribution with confidence
Miao, W. (2023). Specificity analysis for causal inference in observational studies
国家重大人才计划青年学者项目
国家重点研发计划
青年科学家项目，人工智能的因果数学理论、方法与应用， 负责人
国家自然科学基金
面上项目，关于无对照研究和中介分析的因果建模与推断， 主持
数学物理科学部重大项目，融汇海量观测数据的大气系统建模与预报中的关键数学问题与算法，参与
北京市自然科学基金
重点项目，人工智能的统计理论与算法基础， 参与
北京智源人工智能研究院
重大专项，过参数化模型与因果学习的统计理论， 参与
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中国现场统计研究会因果推断分会，副理事长