Regression analysis of group-tested current status data
报告人： 胡涛（首都师范大学）
时间：2025-10-30 15:10-17:00
地点：Room 217, Guanghua Building 2
Abstract:
Group testing is an effective way to reduce the time and cost associated with conducting large-scale screening for infectious diseases. Benefits are realized through testing pools formed by combining specimens, such as blood or urine, from different individuals. In some studies, individuals are assessed only once and a time-to-event endpoint is recorded, for example, the time until infection. Combining group testing with this type of endpoint results in group-tested current status data. To analyse these complex data, we propose methods that estimate a proportional hazard regression model based on test outcomes from measuring the pools. A sieve maximum likelihood estimation approach is developed that approximates the cumulative baseline hazard function with a piecewise constant function. To identify the sieve estimator, a computationally efficient expectationmaximization algorithm is derived by using data augmentation. Asymptotic properties of both the parametric and nonparametric components of the sieve estimator are then established by applying modern empirical process theory. Numerical results from simulation studies show that our proposed method performs nominally and has advantages over the corresponding estimation method based on individual testing results. We illustrate our work by analysing a chlamydia dataset collected by the State Hygienic Laboratory at the University of Iowa.
About the Speaker:
胡涛，首都师范大学数学科学学院教授，博士生导师。研究方向：生物统计、应用统计。在国内外学术刊物Journal of the American Statistical Association、Biometrika、Bioinformatics、Biometrics、Renewable Energy和中国科学：数学等上发表学术论文多篇。主持北京高校卓越青年科学家计划项目、国家自然科学基金面上项目、北京市自然科学基金重点研究专题等多项基金项目。
Your participation is warmly welcomed!
欢迎扫码关注北大统计科学中心公众号，了解更多讲座信息!
