Welcome to our site! Currently, our group's research focuses on adaptive randomization designs and their statistical inference.
More specifically, we are interested in the impact of network interference in A/B testing; unobserved covariates in covariate-adaptive designs; issues in personalized medicine; statistical applications to clinical trials, etc.
We are also interested in the use of AI in clinical trial design.
To adaptive randomize or to rerandomize: comparison of covariate-adaptive randomization and rerandomization.
Ziji Qin*, Feifang Hu and Yang Liu
Estimating treatment and spillover effects with ego-cluster experimental design.
Xiao Liu, Feifang Hu and Jingfei Zhang
Discretization in covariate-adaptive randomization: gains or losses?
Zixuan Zhao*, Feifang Hu
Statistical inference with Mixed effect model for covariate-adaptive randomized experiments
Yang Liu, Lucy Xia, Feifang Hu
SynthIPD: assumption-lean synthetic individual patient data generation
Zixuan Zhao*, Zexin Ren*, Guannan Zhai, Feifang Hu, Will Ma, En Xie, Qian Shi
Valid test for multi-arm trials with GLM under covariate-adaptive randomization
Guannan Zhai, Feifang Hu.
Efficient randomized adaptive designs for multi-arm clinical trials
Norah Alkhnefr, Guannan Zhai, Feifang Hu.