个人简介
耿直，现任北京大学数学科学学院教授，任北京生物医学统计与数据管理研究会理事长。曾荣获国家杰出青年基金、国家教委和人事部全国优秀留学回国人员、国家教委跨世纪优秀人才、全国统计科学研究优秀成果奖一等奖、国家教委科技进步奖二等奖、北京市科技进步二等奖、北京市优秀教师。近5年，主持或参加国家自然科学基金面上项目2项，参加国家高技术研究发展计划（863计划）资助项目 1项，参加科技部973项目1项，参加国家自然科学基金委重大研究计划 1项。
近期论文
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1. Geng, Z., Liu, Y., Liu, C. C. and Miao, W. (2019) Evaluation of causal effects and local structure learning of causal networks. Ann. Rev. Statist. & Appl. 6, 103-124.
2. Geng,Z. (1992) Collapsibility of relative risks in contingency tables with a response variable. J. Royal Statist. Soc. B54, 585-93
3. Geng, Z. and Asano,Ch. (1993) Strong collapsibility of association measures in linear models. J. Royal Statist. Soc. B55, 741-747
4. Guo, J. H. and Geng, Z. (1995) Collapsibility of logistic regression coefficients. J. Royal Statist. Soc. B57, 263-267
5. Geng, Z.，Guo, J. H. and Fung W. K. (2002) Criteria for confounders in epidemiological studies. J. Royal Statist. Soc. B64, 3-15
6. Ma, Z., Xie, X. and Geng Z. (2006) Collapsibility of distribution dependence. J. Royal Statist. Soc. B 68, 127-133.
7. Xie, X., Geng, Z. and Zhao, Q. (2006) Decomposition of structural learning about directed acrylic graphs, Artificial Intelligence 170, 422-439.
8. Chen, H., Geng, Z. and Jia, J. (2007) Criteria for surrogate end points. J. Royal Statist. Soc. B 59, 911-932.
9. Xie, X. and Geng, Z. (2008) A recursive method for structural learning of directed acyclic graphs. J. Machine Learning Research, 9,459-483.
10. Jiang, Z. C., Ding, P. and Geng, Z. (2016) Principal causal effect identification and surrogate endpoint evaluation by multiple trials. J Royal Statist. Soc. B78, 829-848.
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