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.
I have updated definitions in the glossary on this web site and would welcome your comments. Suggestions for new entries are always welcome.
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.
Using structural model semantics, Pearl gives definitions of six counterfactual quantities. More
Suzuki et al. draw the distinction between the attributable cases and attributable proportions in their careful article in Am J Epidemiol. 2012;175(6):567–575.
My colleague, Adrian Levy, presented at the 2012 Harvard-Merck workshop Comparative Effectiveness Research: Controversies and Opportunities. The focus of the Workshop was on statistical, analytical and design methods of comparative effectiveness research in therapeutic interventions. More
AHRQ made available for comments a new publication entitled, Developing a Protocol for Observational Comparative Effectiveness Research: A User’s Guide. This 11-chapter guide is a resource for investigators and stakeholders for developing observational comparative effectiveness research studies. More
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
DAGitty is a GUI tool for constructing and analyzing Causal Diagrams. It was created by Textor and Hardt and is available at dagitty.net
I was presenting today on causal diagrams, and a question came whether the assumption behind an arrow is of associational or causal nature. More
In his engaging book, Understanding Health Services, Prof. Nick Black outlines several reasons. More