报告题目:Variable selection for mixed panel count data under the proportional mean model
报告时间:2023-12-30 09:00-09:30
报 告 人:胡涛 教授 首都师范大学
报告地点:理学院东北楼302
Abstract:Mixed panel count data have
attracted increasing attention in medical research based on event history
studies. When such data arise, one either observes the number of event
occurrences or only knows whether the event has happened or not over an
observation period. In this article, we discuss variable selection in event
history studies given such complex data, for which there does not seem to exist
an established procedure. For the problem, we propose a penalized likelihood
variable selection procedure and for the implementation, an
expectation–maximization algorithm is developed with the use of the coordinate
descent algorithm in the M-step. Furthermore, the oracle property of the
proposed method is established, and a simulation study is performed and indicates
that the proposed method works well in practical scenarios. Finally, the method
is applied to identify the risk factors associated with medical non-adherence
arising from the Sequenced Treatment Alternatives to Relieve Depression Study.