Abstract: The first duty of any epidemiologist is to ask a relevant question. Learning and applying sophisticated epidemiologic methods is of little help if the methods are used to answer irrelevant questions. This talk will discuss the formulation of research questions in the presence of time-varying treatments and treatments with multiple versions, including pharmacological treatments and lifestyle exposures. Several examples will show that discrepancies between observational studies and randomized trials are often not due to confounding, but to the different questions asked.
Brief Biography: Miguel Hernán is Professor of Department of Epidemiology and Department of Biostatistics at the Harvard School of Public Health (HSPH). His research is focused on the development and application of causal inference methods to guide policy and clinical interventions. He and his collaborators apply statistical methods to observational studies under suitable conditions to emulate hypothetical randomized experiments so that well-formulated causal questions can be investigated properly. His research applied to many areas, including investigation of the optimal use of antiretroviral therapy in patients infected with HIV, assessment of various interventions of kidney disease, cardiovascular disease, cancer and central nervous system diseases. He is Associate Director of HSPH Program on Causal Inference in Epidemiology and Allied Sciences, member of the Affiliated Faculty of the Harvard-MIT Division of Health Sciences and Technology, and an Editor of the journal EPIDEMIOLOGY. He is the author of upcoming highly anticipated textbook "Causal Inference" (Chapman & Hall/CRC, 2013), drafts of selected chapters are available on his website.