Our foray into causal analysis is not yet complete. Until we define the methods of causal inference, we can't get to the deeper insights that causal analysis can provide. This article details many of ...
Yılmaz, Övünç; Son, Yoonseock; Shang, Guangzhi; Arslan, Hayri A. Causal inference under selection on observables in operations management research: Matching methods and synthetic controls. Journal of ...
In the article that accompanies this editorial, Lu et al 5 conducted a systematic review on the use of instrumental variable (IV) methods in oncology comparative effectiveness research. The main ...
Faculty develop methods for structured and unstructured biomedical data that advance statistical inference, machine learning, causal inference, and algorithmic modeling. Their work delivers principled ...
The aim of this research therefore was to streamline the understanding of typical causal structures in both randomized and nonrandomized clinical trials in oncology, presenting concise guidelines for ...
Machine learning algorithms are widely used for decision making in societally high-stakes settings from child welfare and criminal justice to healthcare and consumer lending. Recent history has ...
Results that may be inaccessible to you are currently showing.
Hide inaccessible results
Feedback