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 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 ...

Health researchers need to fully understand the underlying assumptions to uncover cause and effect. Timothy Feeney and Paul Zivich explain Physicians ask, answer, and interpret myriad causal questions ...

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 ...

First, we would like to congratulate the authors for successfully hosting the causal inference data competition (referred to as Competition henceforth) and contributing a unique and thought-provoking ...

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 ...

This course is available on the MSc in Applied Social Data Science, MSc in Behavioural Science, MSc in Human Geography and Urban Studies (Research), MSc in Innovation Policy, MSc in International ...

Dorie and co-authors (DHSSC) are to be congratulated for initiating the ACIC Data Challenge. Their project engaged the community and accelerated research by providing a level playing field for ...