講座主題：Semiparametric Bayesian analysis of accelerated failure time models with cluster structures
專家姓名：沈俊山
工作單位：首都經(jīng)貿(mào)大學(xué)
講座時(shí)間：2017年7月28日10:10
講座地點(diǎn)：數(shù)學(xué)院大會(huì)議室
主辦單位：煙臺大學(xué)數(shù)學(xué)與信息科學(xué)學(xué)院
內(nèi)容摘要：
In this talk, we develop a Bayesian semiparametric AFT model for survival data with cluster structures (BSP-DRM). We show through both simulation studies and analysis of Mayo clinic trial in PBC that the information pooling can significantly improve the efficiency of estimating regression coefficients in the AFT models. Moreover, the flexible accommodation of distributional heterogeneity greatly reduces potential estimation biases, and also improves estimation efficiency when the distributions of different clusters have different shapes.
主講人介紹：
蘭州大學(xué)碩士,、北京大學(xué)博士,；主要從事生存分析,、不完全數(shù)據(jù)分析,、經(jīng)驗(yàn)似然、 半?yún)?shù)模型推斷,、 Bayes 統(tǒng)計(jì)學(xué)等方面的研究. 在 J. Amer. Statist. Assoc.,、Comput. Statist.、Data Anal.,、Statist. Papers,、 Ann. Inst. Statist. Math.、 J. Multivariate Anal.,、Statist. Probab. Lett.等國際著名學(xué)術(shù)刊物發(fā)表論文16篇. 主持完成了國家自然科學(xué)基金青年基金項(xiàng)目和博士后基金項(xiàng)目.
