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Recently, the team of Professor Zhou Xiaohua from the Department of Biostatistics of Peking University School of Public Health and Beijing International Mathematics Research Center has achieved two outstanding results in the research of causal inference in the clinical field
.
The first result is the study of causal inference on observational data
.
This study proposes a new estimation and inference method that uses high-dimensional covariates and the heterogeneous local causal effects of observed data, without the strong negligibility assumption used in conventional causal inference
Article link: https://rss.
onlinelibrary.
wiley.
com/doi/full/10.
1111/rssb.
12469
(The impact of medical assistance on the outcome of heterogeneous treatment)
In addition, the team of Professor Xiaohua Zhou and Assistant Professor Miao Wang has also achieved outstanding results in the fusion of clinical trial data
.
Randomized controlled trials (RCT) are the gold standard for evaluating the safety and effectiveness of clinical drugs.
However, due to high trial costs and strict recruitment conditions, the lack of sufficient sample size is often the most important factor restricting the efficiency and accuracy of causal inference One of
The study discussed how to introduce external control data into clinical trials to improve the efficiency and estimation accuracy of causal inference, and proposed a bi-robust statistical method that can reach the lower bound of semi-parametric efficiency
.
The above statistical methods can make full use of information from different sources of data, and only need part of the working model to be correctly set to give a consistent estimate
Article link: https://doi.
org/10.
(Peking University School of Public Health)
