Description:

Randomized controlled trials are the gold standard for medical research. However, intercurrent events complicate the analysis and interpretation of randomized controlled trials. The ICH E9(R1) Addendum provides some guidance, which is far from clear and solid. I will discuss the causal inference perspective on randomized controlled trials with intercurrent events.

Prerequisite: Basic probability and statistics

Reference:

Ding, P. (2024) A first course in causal inference. Chapman & Hall.  

Jiang, Z., Yang, S. and Ding, P. (2022). Multiply robust estimation of causal effects under principal ignorability. Journal of the Royal Statistical Society, Series B, 84, 1423-1445. 

Lu, S., Yi, Y., Qu, Y., Liu, H. K., Ye, T. and Ding, P. (2025) Estimating treatment effects with competing intercurrent events in randomized controlled trials.

Target Audience: Undergraduate students, Graduate students

Teaching Language: Chinese

Bio:

Peng Ding is an Associate Professor in the Department of Statistics at UC Berkeley.
He obtained my Ph.D. from the Department of Statistics, Harvard University in May 2015 and worked as a postdoctoral researcher in the Department of Epidemiology, Harvard T. H. Chan School of Public Health until December 2015. Previously, he received his B.S. in Mathematics, B.A. in Economics, and M.S. in Statistics from Peking University.

Registration: https://www.wjx.top/vm/OkwGMZ2.aspx#