Diginomica

How causal analysis and AI intersect - methods of causal inference

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 ...
JSTOR Daily

Brief Report: Repair of Partly Misspecified Causal Diagrams

Errors in causal diagrams elicited from experts can lead to the omission of important confounding variables from adjustment sets and render causal inferences invalid. In this report, a novel method is ...
JSTOR Daily

Instrumental variables as bias amplifiers with general outcome and confounding

Drawing causal inference with observational studies is the central pillar of many disciplines. One sufficient condition for identifying the causal effect is that the treatment-outcome relationship is ...
BMJ

Physical activity and longevity: how to move closer to causal inference

Correspondence to Dr Kaitlin H Wade, Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK; Kaitlin.Wade{at}bristol.ac.uk Kujala provides an insightful review contesting ...
CMAJ

Testing group differences for confounder selection in nonrandomized studies: flawed practice

Using observed imbalances between study groups (e.g., exposed and unexposed) to determine variables for confounding adjustment in nonrandomized studies may misguide the selection of variables to ...