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有序回归中的残差分析
澳门新葡8455最新网站:2017年04月26日 11:26 点击数:

报告人:张和平

报告地点:澳门新葡8455最新网站501室

报告澳门新葡8455最新网站:2017年05月04日星期四10:00-11:00

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报告摘要:

Ordinal outcomes are common in scientific research and everyday practice, and we often rely on regression models to make inferences. A long-standing problem with such regression analyses is the lack of effective diagnostic tools for validating model assumptions. The difficulty arises from the fact that an ordinal variable has discrete values that are labeled with, but not, numerical values. The values merely represent ordered categories. In this paper, we propose a surrogate approach to defining residuals for an ordinal outcome $Y$. The idea is to define a continuous variable $S$ as a ``surrogate'' of $Y$ and then obtain residuals based on $S$. For the general class of cumulative link regression models, we study the residual's theoretical and graphical properties. We show that the residual has null properties similar to those of the common residuals for continuous outcomes. The proposed residual also enables us to develop numeric measures for goodness-of-fit using classical distance notions. Our results suggest that compared to a previously defined residual, our residual can reveal deeper insights into model diagnostics.

主讲人概况:

张和平,世界著名统计学家,博士毕业于斯坦福大学,现为耶鲁大学生物统计学终身教授,国家千人计划特聘专家,中山大学长江学者讲座教授。美国统计协会与国际数理统计协会fellow。2008年被授予哈佛大学公共卫生新葡京最新官网的Myrto Lefokopoulou Distinguished Lecturer,2011年被授予国际数理统计协会的Medallion Lecturer,2011年获得生殖医学的国际Royan Award。同时兼职中国科新葡京最新官网统计科学中心学术委员会副主任。主持多项超千万美金的美国卫生科学研究院(NIH)的国家重要项目。在统计学、医学、遗传学等领域发表论文近300篇,多篇论文发表在New England Journal of Medicine,Proceedings of the National Academy of Sciences USA,American Journal of Human Genetics,American Journal of Obstetrics and Gynecology,International Journal of Cancer,Bioinformatics,以及统计学“四大天王”杂志JASA,Annals of Statistics,JRSSB,Biometrika。

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