Framework for drawing causal inference from observational studies:
Is there a way to graphically depict two intervening variables that influence each other in a DAG? By definition, it is clear that a DAG is acyclic and cannot include bi-directional arrows. Yet, I wonder if there is way to allow for the inclusion of this type of relationship in a causal model.
Thank-you! More
Preparing a presentation at SPPH, I used Pearl’s counterfactual probabilities in the context of coronary revascularization.
In the patient care setting, we can only observe one possible treatment and one potential outcome for a given patient. Therefore, establishing the causal effect of treatment requires comparing the observed outcome and counterfactual outcome (i.e. a potential outcome for a counterfactual treatment).
I was presenting on the causal perspective in CER today, and a question came about connection between the claim that deaths are attributed to exposure and the claim that these deaths could be avoided had the exposure been eliminated. More
I was presenting today on causal diagrams, and a question came whether the assumption behind an arrow is of associational or causal nature. More
Causal reasoning could be narrowed to deducing the causal effect from a set of conditional probabilities defining joint variation of random variables.