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Causal inference in epidemiology: recent methodological developments 10-14 November 2014 London School of Hygiene & Tropical Medicine http://www.lshtm.ac.uk/study/cpd/causal_inference.html ____________________________________________________________________________ COURSE ORGANISERS Bianca De Stavola, Simon Cousens, Rhian Daniel Guest lecturer: Stijn Vansteelandt (Ghent University, Belgium) THE COURSE Most courses on statistical modelling in epidemiology concentrate on the use of regression models to estimate causal effects while adjusting for measured confounders. These address uncertainty due to sampling error but not, in general, other sources of error and uncertainty which may arise from missing data, measurement error, uncontrolled confounding, and/or selection bias. Recent methodological advances make it feasible to incorporate at least some of these sources of error into statistical models so that quantitative assessments can be made of their impact on estimates of causal effect and the uncertainty around those estimates. The course will discuss the current state of the art with respect to these issues, while retaining a practical focus. Participants will acquire awareness of the common threads across these new methods and competence in applying them in simple settings using Stata. FOR MORE INFORMATION: http://www.lshtm.ac.uk/study/cpd/causal_inference.html Centre for Statistical Methodology http://csm.lshtm.ac.uk/ You may leave the list at any time by sending the command SIGNOFF allstat to [log in to unmask], leaving the subject line blank.