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报告题目:医疗数据和当前发展的生存分析(Survival analysis for medical data and current developments)
发布时间:2018-05-11 | 浏览次数: | 来源:杨继盛
 

报告人:Jun Ma

工作单位:麦考瑞大学

报告时间:2018年5月17日(星期四)9:00

报告地点:管理学院一楼1111会议室

 

报告人简介

Jun Ma received the B.Sc. degree in mathematics from Anhui University, Anhui, China, in 1983 and the M.App.Stat. and Ph.D. degrees in statistics from Macquarie University, Sydney, Australia in 1991 and 1996 respectively. He is currently with the Department of Statistics, Macquarie University. His research interests include survival analysis, statistical computations with big data, medical imaging, image restoration, generalized linear models and semi-parametric regression models. So far, he has supervised more than 15 PhD students and more than 30 Masters students.

报告简介

Survival analysis provides important approaches for analysing medical data. Particularly, Cox's regression model plays a pivotal rule in survival analysis. In this talk, we will start with a quick introduction to survival analysis and the Cox model, with examples to explain how this model can be used in analysing medical data. Then, after pointing out shortcomings of the partial likelihood method for Cox model fitting, we will proceed to recent developments of likelihood based methods. A simulation study will be included to compare several methods, and finally a real melanoma data example will be explained.

 

 
 
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