报告人：栗家量（新加坡国立大学）

时间：2021年12月24日10:30

腾讯会议ID：558 124 636

会议链接：https://meeting.tencent.com/dm/iBZXa09pwEur 

摘要：Forecasting survival risks for time-to-event data is an essential task in clinical research. Practitioners often rely on well-structured statistical models to make predictions for patient survival outcomes. The nonparametric proportional hazards model, as an extension of the Cox proportional hazards model, involves an additive nonlinear combination of covariate effects for hazards regression and may be more flexible. When there are a large number of predictors, nonparametric smoothing for different variables cannot be simultaneously optimal using the conventional fitting program. To address such a limitation and still maintain the nonparametric flavor, we present a novel model averaging method to produce model-based prediction for survival outcome and our method automatically offers optimal smoothing for individual nonparametric functional estimation. The proposed semiparametric model averaging prediction (SMAP) method basically approximates the underlying unstructured nonparametric regression function by a weighted sum of low-dimensional nonparametric sub-models. The weights are obtained from maximizing the partial likelihood constructed for the aggregated model. Theoretical properties are discussed for the estimated model weights. Simulation studies are conducted to examine the performance of SMAP under various evaluation criteria. Two real examples from genetic research studies motivated our work and are analyzed by the proposed SMAP to produce new scientific findings.

简介:栗家量，新加坡国立大学统计与数据科学系教授，同时担任杜克大学-新加坡国立大学医学院及新加坡眼科研究所的兼职教授。栗教授本科毕业于中科科学技术大学，博士毕业于美国威斯康大学。栗教授已发表科研论文160余篇, 主要学术成果发表在Annals of Statistics, JASA, Biometrics, Journal of Econometrics, JBES等统计学顶级杂志上。他最近的研究方向包括诊断医学，精准医学，非参数方法，统计学习与生存分析。他与合作者著有一本Chapman & Hall CRC Press于2013年出版的专著Survival Analysis in Medicine and Genetics。 他的论文总引用量达到3700，h-index 32。他在Biometrics 和 Lifetime data Analysis等统计杂志担任过副主编。他曾获得新加坡国立大学的Young Scientist Award, 他也是美国统计学会(ASA)的会士(Fellow)和国际统计所(ISI)的选举会员(Elected member).

邀请人：夏小超

欢迎广大师生积极参与！