Southwest Jiaotong University School of Mathematics

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新加坡国立大学统计系栗家量教授学术报告

来源:   作者:黄磊     日期:2018-09-03 16:11:05   点击数:  

报告人简介: Jialiang Li, 博士毕业于威斯康辛-麦迪逊大学,新加坡国立大学教授,副系主任(科研), 栗教授长期从事数理统计学、生物统计学的理论和应用研究,以第一作者或通讯作者身份发表包括The Annals of Statistics, Journal of the American Statistical Association在内的统计学顶级期刊文章,以及Statistics in Medicine, Biometrics, Biostatistics, Statistical Methods in Medical Research等生物、医学统计顶级期刊文章数十余篇,连同合作发表的文章,总数高达百余篇。栗教授所研究内容包括非参数半参数统计模型,函数型数据研究,医疗大数据分析,深度学习,多分类医学检验,变点模型等等,其研究内容多与实际问题结合密切,栗教授先后主持科研项目金额超120万新加坡币,折合人民币600余万元,栗教授参与的重大医学研究项目有近200万新加坡币,折合人民币1000万元。

报告地点:X2511

报告时间:201896日周四,上午10:30

报告题目:Multi-category Diagnostic Accuracy based on Logistic Regression

摘要: We provide a detailed review for the statistical analysis of diagnostic accuracy in a multi-category classification task. For qualitative response variables with more than two categories, many traditional accuracy measures such as sensitivity, specificity and area under the ROC curve are no longer applicable. In recent literature new diagnostic accuracy measures are introduced in medical research studies. In this paper, important statistical concepts for multi-category classification accuracy are reviewed and their utilities are demonstrated with real medical examples. We offer problem based R code to illustrate how to perform these statistical computations step by step. We expect such analysis tools will become more familiar to practitioners and receive broader applications in biostatistics. Our program can be adapted to many classifiers among which logistic regression may be the most popular approach. We thus base our discussion and illustration completely on the logistic regression in this paper.