Biosketch
Yuxin obtained her master degree from National University of Singapore majoring in Statistics after gained the bachelor degree from Beihang Universitiy, school of Mathematics.
Now she is a PhD candidate at the Institute of AI in Management, LMU Munich, under the supervision of Prof. Stefan Feuerriegel.
relAI Research
Constructing Confidence Intervals for Average Treatment Effects from Multiple Datasets
Constructing confidence intervals (CIs) for the average treatment effect (ATE) from patient records is crucial to assess the effectiveness and safety of drugs. However, patient records typically come from different hospitals, thus raising the question of how multiple observational datasets can be effectively combined for this purpose. In our paper, we propose a new method that estimates the ATE from multiple observational datasets and provides valid CIs. Our method makes little assumptions about the observational datasets and is thus widely applicable in medical practice. The key idea of our method is that we leverage prediction-powered inferences and thereby essentially `shrink’ the CIs so that we offer more precise uncertainty quantification as compared to naïve approaches. We further prove the unbiasedness of our method and the validity of our CIs. Finally, we provide an extension of our method for constructing CIs from combinations of experimental and observational datasets.