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 ...
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 ...
Dr Vanessa Didelez is a statistician developing methods to understand better causal mechanisms, the processes linking cause and effect in complex systems in motion that evolve over time, so-called ...
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 ...
Repeated measurements of the same countries, people, or groups over time are vital to many fields of political science. These measurements, sometimes called time-series cross-sectional (TSCS) data, ...
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 ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback