JSM 2012 Online Program
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Online Program HomeActivity Details
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| CE_08C | Sun, 7/29/2012, 8:30 AM - 5:00 PM | HQ-Indigo E | |
| Targeted Learning: Causal Inference for Observational and Experimental Data — Continuing Education Course | |||
| ASA | |||
| Instructor(s): Maya Petersen, University of California at Berkeley School of Public Health, Sherri Rose, Johns Hopkins Bloomberg School of Public Health, Mark van der Laan, University of California at Berkeley School of Public Health | |||
| This course concerns statistical methods for causal inference using observational and experimental point treatment and longitudinal data. Attendees will learn both the application of and theory behind methodological advances for causal inference. A review and scientific critique of current estimation will be provided, including an introduction to targeted learning. Structural causal models (causal graphs) and working marginal structural models will be introduced as tools for translating a policy or research question and background knowledge into a target statistical quantity and model. The course will emphasize understanding and responding to the challenges posed by randomized controlled trials and observational cohorts, including informative drop-out/censoring, missing data, time-dependendent confounding, and high dimensional covariates. Examples from the areas of HIV research and the epidemiology of aging, together with other fields, will be used as illustrations and will provide practical experience with analytic design and accurate interpretation of results. Anticipated audience will include statisticians with a strong background in maximum likelihood estimation and possible previous exposure to causal assumptions, e.g., Chapters 1, 2, 4.1-4.4, and 7 in "Causality" by Pearl. Course content covers material from Chapters 1-7, 9, 10, and 16-18 of "Targeted Learning" by van der Laan & Rose, as well as additional advances. | |||
2012 JSM Online Program Home
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