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 ...
The past decade has witnessed significant advances in causal inference and Bayesian network learning, two intertwined disciplines that allow researchers to discern underlying cause‐and‐effect ...
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 ...
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 ...
In the quest to unravel the underlying mechanisms of natural systems, accurately identifying causal interactions is of paramount importance. Leveraging the advancements in time-series data collection ...
This article considers causal inference for treatment contrasts from a randomized experiment using potential outcomes in a finite population setting. Adopting a Neymanian repeated sampling approach ...
Company will showcase scientific leadership with three key presentations and highlights scalable, data-agnostic research solutions at ISPE Annual Conference 2025. With a strong emphasis on causal ...
Setodji CM, McCaffrey DF, Burgette LF, Almirall D, Griffin BA. The right tool for the job: Choosing between covariate balancing and generalized boosted model propensity scores. Epidemiology. 2017.
Joshua Angrist GS ’89 was awarded the 2021 Nobel Prize in Economics. He won half of the prize jointly with Guido Imbens “for their methodological contributions to the analysis of causal relationships.
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