|Other - Pasquale Porcelli Lecture|
|Adaptive Confidence Intervals for Non-smooth Parameters|
|Susan Murphy, University of Michigan|
|H.E. Robbins Professor of Statistics & Professor of Psychiatry, Research Professor, Institute for Social Research|
|Digital Media Center Theatre
April 28, 2014 - 04:30 pm
Non-regular, aka "non-smooth" parameters are of scientific interest occur frequently in modern day inference. In particular when scientific
My current primary interest concerns clinical trial design and the development of data analytic methods for informing multi-stage decision making in health. In particular for (1) constructing individualized sequences of treatments (a.k.a., adaptive interventions) for use in informing clinical decision making and (2) constructing real time individualized sequences of treatments (a.k.a., Just-in-Time Adaptive Interventions) delivered by mobile devices. See Workshop on Just in Time Adaptive Interventions. Adaptive Interventions, also known as dynamic treatment regimes, are composed of a sequence of decision rules that specify when to alter the therapy and specify which intensity or type of subsequent therapy should be offered. The decision rules employ variables such as patient response, risk, burden, adherence, and preference, collected during prior therapy. These regimes hold the promise of maximizing treatment efficacy by avoiding ill effects due to over-treatment and by providing increased treatment levels to those who can benefit.