Regression analysis of informative current status data with the semiparametric linear transformation model

发布时间：2019-06-13 作者：浏览次数：

Speaker:	赵世舜	DateTime:	2019年6月17日（周一）下午4：15-5：00
Brief Introduction to Speaker: 赵世舜，吉林大学数学学院教授、博士生导师。		Place:	六号楼二楼报告厅
Abstract:In this paper, we consider a general class of semiparametric linear transformation models and develop a sieve maximumlikelihood estimation approach for the inference. In the method, the copula model is employed to describe the informative censoring or relationship between the failure time of interest and the censoring time, and Bernstein polynomials are used to approximate the nonparametric functions involved. The asymptotic consistency and normality of the proposed estimators are established, and an extensive simulation study is conducted and indicates that the proposed approach works well for practical situations. In addition, an illustrative example is provided.