Academic Report of School of Mathematical Sciences [2026] No. 066

(Series Report for High-Level University Construction No. 1325)

Title：Orthogonalized Score Tests for Conditional Variable Significance in Deep Partial Linear Cox Models

Speaker：Meiling Hao, Professor (University of International Business and Economics)

Time：14:30-15:30, June 29, 2026

Location：Conference Room 514, Huixing Building, Yuehai Campus, Shenzhen University

Abstract: Conditional statistical inference for high-dimensional survival data remains a fundamental yet challenging problem, particularly when the effects of nuisance variables are complex and difficult to specify parametrically. In this paper, we propose a Deep Partial Linear Cox model that leverages neural networks to flexibly capture nonlinear nuisance effects while preserving interpretability for variables of primary interest. To test the conditional significance of high-dimensional variable sets within this framework, we develop an orthogonalized score test that effectively removes the influence of estimated nuisance components, thereby achieving valid inference in the presence of complex data dependencies. Our method accommodates settings where the number of tested parameters exceeds the sample size, without imposing sparsity assumptions. We establish the limiting null distribution of the proposed test statistic. Extensive numerical studies and an application to the TCGA breast cancer dataset demonstrate the superior performance and practical utility of our approach.

Speaker Profile：Meiling Hao is a professor at the University of International Business and Economics. She holds a Ph.D. from the Hong Kong Polytechnic University and completed a postdoctoral fellowship at the Princess Margaret Cancer Research Center. Her primary research areas include high-dimensional data analysis, biostatistics, nonparametric statistics, and reinforcement learning. She has led projects funded by the National Natural Science Foundation of China’s Young Scientists Program and General Program, and her academic papers have been published in journals such as the Journal of the American Statistical Association, Journal of Machine Learning Research, Statistica Sinica, The Electronic Journal of Statistics, Computational Statistics & Data Analysis, and Statistical Methods in Medical Research.

Faculty and students are welcome to attend!

Invited by: Zongliang Hu

School of Mathematical Sciences

June 25, 2026