The Division of Science and Technology (DST) held a lecture on “Propensity Score-based Spline Approach for Average Causal Effects” with guest speaker Professor Xingwei Tong on April 1, 2021. Prof. Tong illustrated the optimization model of causal inference based on the international causal inference, and delivered its application in precision medicine.

Prof. Tong giving a lecture

Prof. Tong is the Head of the Department of Mathematical Statistics at Beijing Normal University. He is a well-known scholar in biostatistics and financial statistic, and a managing member of National Statistical Society of China and Chinese Society of Probability and Statistics.

Firstly, Prof. Tong elaborated common methods of the international causal inference and analyzed the existing problems of the methods by the case of “Tai Chi movement and life extension”. To solve these practical issues, the average treatment effect and strong neglect hypothesis have been proposed internationally. Furthermore, Prof. Tong illuminated the concept of propensity scores and talked about transforming high-dimensional influencing factors into one-dimensional problems.

A strong academic atmosphere

Subsequently, Prof. Tong pointed out the three problems of the existing causal analysis model and proposed a new optimization model to solve these problems. In the case analysis of “the relationship between purchasing insurance and the willingness to the hospital”, Prof. Tong compared the proposed new method with international methods. The results of the new method are more closely matched with the actual situation.

Q&A session

At the end of the lecture, Prof. Tong interacted with the audience and answered their questions. During the Q&A session, he gave a more in-depth explanation of the new model.

Prof. Kaitai Fang (right) presenting UIC souvenirs

Prof. Tong and UIC teachers

Reporter: Xinhui Liu

Photographers: Xinhui Liu & Hongyi Lu

Editors: Garbo Hu & Quincy Zhang

(From STAT Programme)