Causal inference in observational settings seeks to estimate the effect of exposures, treatments or interventions on outcomes in the absence of random assignment. Unlike experimental designs, ...

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 ...

Causal inference is important in medical research to help determine if treatments are beneficial and if natural exposures are harmful. In many settings, data collection makes causal inference ...

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 ...

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 ...

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 ...

A new study links increased plastic waste imports to measurable increases in PM2.5 near waste disposal sites in Indonesia.