JSM 2015 Preliminary Program

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Legend: Washington State Convention Center = CC, Sheraton Seattle = S, Grand Hyatt = GH and The Conference Center = TCC
* = applied session       ! = JSM meeting theme

Activity Details

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CE_20C Tue, 8/11/2015, 8:00 AM - 12:00 PM S-Grand Ballroom D
Dynamic Treatment Regimes, Sequentially Randomized Trials, and Causal Inference (ADDED FEE) — Professional Development Continuing Education Course
ASA , Biometrics Section
Effective treatment of many chronic disorders such as mental illnesses, cancer, and HIV infection typically requires ongoing medical intervention in which clinicians sequentially make therapeutic decisions, adapting the type, dosage, and timing of treatment according to patient characteristics. Dynamic treatment regimes (DTRs) operationalize the sequential decisionmaking process in the personalized clinical practice. Constructing evidence-based DTRs from either observational or sequentially randomized trials comprises an important and challenging methodological area of statistical research. This half-day course will provide a comprehensive description of the field. We will begin with a discussion of relevant data sources (multi-stage sequentially randomized trials and longitudinal observational studies) and their relative advantages, as well as considerations for designing efficient studies that can produce high-quality data to aid the construction of DTRs. We will then turn our attention to estimation via a popular method called Q-learning. Next, we will consider inferential challenges in this area, and present some state-of-the-art methods for doing inference. We will cover a practical demonstration of estimation of optimal DTRs using Q-learning and associated inference, applying the R package qLearn. Finally, we will give a relatively quick overview of alternative estimation approaches.
Instructor(s): Erica Moodie, McGill University, Bibhas Chakraborty, Duke University




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