6 papers · 1 filter
Integrating Heterogeneous Information in Randomized Experiments: A Unified Calibration Framework
Wei Ma, Zeqi Wu, Zheng Zhang
In modern randomized experiments, large-scale data collection increasingly yields rich baseline covariates and auxiliary information from multiple sources. Such information offers…
A General (Non-Markovian) Framework for Covariate Adaptive Randomization: Achieving Balance While Eliminating the Shift
Hengjia Fang, Wei Ma
Emerging applications increasingly demand flexible covariate adaptive randomization (CAR) methods that support unequal targeted allocation ratios. While existing procedures can ach…
On the achievability of efficiency bounds for covariate-adjusted response-adaptive randomization
Jiahui Xin, Wei Ma
In the context of precision medicine, covariate-adjusted response-adaptive randomization (CARA) has garnered much attention from both academia and industry due to its benefits in p…
Incorporating external data for analyzing randomized clinical trials: A transfer learning approach
Yujia Gu, Hanzhong Liu, Wei Ma
Randomized clinical trials are the gold standard for analyzing treatment effects, but high costs and ethical concerns can limit recruitment, potentially leading to invalid inferenc…
Treatment effect estimation under covariate-adaptive randomization with heavy-tailed outcomes
Hongzi Li, Wei Ma, Yingying Ma +1
Randomized experiments are the gold standard for investigating causal relationships, with comparisons of potential outcomes under different treatment groups used to estimate treatm…
Inference under covariate-adaptive randomization with many strata
Jiahui Xin, Hanzhong Liu, Wei Ma
Covariate-adaptive randomization is widely employed to balance baseline covariates in interventional studies such as clinical trials and experiments in development economics. Recen…