Resources for Causal Reasoning in Health Services Research

Bidirectional arrows in DAGs

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

Causal perspective in CER

Preparing a presentation at SPPH, I used Pearl’s counterfactual probabilities in the context of coronary revascularization.



I have updated definitions in the glossary on this web site and would welcome your comments. Suggestions for new entries are always welcome.

Effect of treatment on treated

Heckman et al. (1997b) have argued that in a variety of policy contexts, it is the average treatment effect for the treated that is of substantive interest. The essence of their argument is that in deciding whether a policy is beneficial, the interest is whether it is beneficial for those individuals who are either assigned or who would assign themselves to the treatment, rather than whether on average the program is beneficial for all individuals.

Counterfactuals and CER

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).

Attribution in causal reasoning

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


DAGitty is a GUI tool for constructing and analyzing Causal Diagrams. It was created by Textor and Hardt and is available at

Assumptions in causal graphs

I was presenting today on causal diagrams, and a question came whether the assumption behind an arrow is of associational or causal nature. More

Message from the literature

Causal reasoning could be narrowed to deducing the causal effect from a set of conditional probabilities defining joint variation of random variables.

Browsing Conrady Science

I have recently received an email from Conrady Science inviting me to their webinar series on Bayesian Networks. On their website I found a plethora of educational materials, which seems like it could be useful for developing an understanding of causal reasoning. More