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 ...

The majority of recent empirical papers in operations management (OM) employ observational data to investigate the causal effects of a treatment, such as program or policy adoption. However, as ...

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 ...

Root-cause analysis is core to problem-solving across many fields. From hospitals searching for patient safety issues to engineers diagnosing faults in complex machinery, finding the source of a ...

The surge in enterprise AI has fueled interest in causal analysis. In this piece, I explore the threads that bind cause and effect - and how they can be applied across a range of industry scenarios.

Which of temperature or food is more important for the richness of deep-sea animals? Dr Moriaki YASUHARA from the School of Biological Sciences, the Research Division for Ecology & Biodiversity, and ...

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 ...