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 ...
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 ...
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 ...
We know that correlation does not imply causation, but careful analyses of correlations are often our only way to quantify cause and effect in domains ranging from healthcare to education. This ...
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 ...
Decades of research have established a significant link between physical activity and health, influencing agenda setting, policy making and community awareness.1–4 However, the field continues to ...
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 ...
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