题目：Quantile Regression for Survival Data with Covariates Subject to Detection Limits

报告人：新加坡南洋理工大学 Xiang Liming 教授

Abstract :With advances of biomedical research, biomarkers are becoming increasingly important prognostic factors for predicting overall survival, while the measurement of biomarkers is often censored due to instruments' lower limits of detection. This leads to two types of censoring: random censoring in overall survival outcomes and fixed censoring in biomarker covariates, posing new challenges in statistical modeling and inference. Existing methods for analyzing such data focus primarily on linear regression ignoring censored responses or semiparametric accelerated failure time (AFT) models with covariates under detection limits (DL). We propose a quantile regression for survival data with covariates subject to DL. To estimate the quantile process of regression coefficients, we develop a novel multiple imputation approach based on another quantile regression for covariates under DL, avoiding stringent parametric restrictions on censored covariates as often assumed in the literature. Under regularity conditions, we show that the estimation procedure yields uniformly consistent and asymptotically normal estimators. Simulation results demonstrate the satisfactory finite-sample performance of the method. We also apply our method to the motivating data from a study of genetic and inflammatory markers of Sepsis.     

时间：2019年7月4日（周四) 下午2:30

地点：565net必赢客户端本部教二楼827教室

联系人：胡涛

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