SSC 2010 Annual Meeting

SSC 2010 Annual Meeting

May 23 2010

Québec, QC



Causal directed acyclic graphs (DAGs) can be used to summarize, clarify, and communicate one’s qualitative assumptions about the causal structure of a problem. The use of causal DAGs is a natural and simple approach to causal inference from observational data. It is also a rigorous approach that leads to mathematical results that are equivalent to those of counterfactual theory. As a result, causal DAGs are increasingly used in epidemiologic research and teaching.

The first part of this workshop will provide a non-technical overview of causal DAGs theory, its relation to counterfactual theory, and its applications to causal inference. It will describe how causal DAGs can be used to propose a systematic classification of biases in observational and randomized studies.

The second part of this workshop will present practical applications of causal DAGs theory to examples taken from various research areas in epidemiology, including cancer, pregnancy outcomes, and HIV/AIDS. It will also describe the bias induced by the use of conventional statistical methods for the analysis of longitudinal studies with time-varying exposures.