学术交流
学术交流
首页  >  学术科研  >  学术交流  >  正文

    Empirical likelihood-based inferences for the area under the ROC curve with covariates

    2014-12-15 办公室 点击:[]

    报告人:杨宝莹

     

    报告摘要:In the receiver operating characteristic (ROC) analysis, the area under the ROC curve (AUC) isa popular summary index of discriminatory accuracy of a diagnostic test. Incorporating covariates into ROCanalysis can improve the diagnostic accuracy of the test. Regression model for the AUC is a tool to evaluate theeffects of the covariates on the diagnostic accuracy. In this paper, empirical likelihood (EL) method is proposedfor the AUC regression model. For the regression parameter vector, it can be shown that the asymptoticdistribution of its EL ratio statistic is a weighted sum of independent chi-square distributions. Confidenceregions are constructed for the parameter vector based on the newly developed empirical likelihood theorem, aswell as for the covariate-specific AUC. Simulation studies were conducted to compare the relative performanceof the proposed EL-based methods with the existing method in AUC regression. Finally, the proposed methodsare illustrated with a real data set.

     

    报告人简介:杨宝莹,女,2011. 1-至今金沙威尼斯欢乐娱人城任教

    教育经历:

    2006. 9-2010. 12        四川大学金沙威尼斯欢乐娱人城获博士学位

     (期间2008. 1-2010. 1 公派到美国佐治亚州立大学数学与统计系学习深造)

    2003. 9-2006. 7        四川大学金沙威尼斯欢乐娱人城获硕士学位

    1999. 9-2003. 7        四川大学金沙威尼斯欢乐娱人城获学士学位

     

     

    报告时间:20141216日下午2:00-4:00

    报告地点:金沙威尼斯欢乐娱人城会议室X2511

    上一条:2014-2015学年第2学期金沙威尼斯欢乐娱人城创新讲座系列
    下一条:Cluster tilting和2-Calabi-Yau tilting理论

    关闭

Baidu
sogou