Statistics Seminar Speaker: Walter Dempsey, 12/07/2018

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Friday Dec 07 2018

Statistics Seminar Speaker: Walter Dempsey, 12/07/2018

10:15am @ G01 Biotechnology

The Statistics Seminar speaker for Friday, December 7, 2018, is Walter Dempsey, a postdoctoral research fellow in the Department of Statistics at Harvard University, advised by Susan Murphy. He received his PhD in Statistics from the University of Chicago, advised by Peter McCullagh. In his research, he tries to think carefully about matters of fundamental importance in the application of statistical methods to substantive scientific problems.  His current work involves three complementary research themes: (1) experimental design and data analytic methods to inform multi-stage decision making in health; (2) statistical modeling of complex longitudinal and survival data; and (3) statistical modeling of complex relational structures such as interaction networks.

Talk: The stratified micro-randomized trial design: sample size considerations for testing nested causal effects of time-varying treatment

Abstract: Technological advancements in the field of mobile devices and wearable sensors have helped overcome obstacles in the delivery of care, making it possible to deliver behavioral treatments anytime and anywhere. Delivery of these treatments is increasingly triggered by detections/predictions of vulnerability and receptivity, which may have been impacted by prior treatments. Furthermore the treatments are often designed to have an impact on users over a span of time during which subsequent treatments may be provided. In this talk, I will discuss the design of a mobile health smoking cessation intervention study with the goal of assessing whether reminders, delivered at times of stress, result in a reduction/prevention of stress in the near-term, and whether this effect changes with time in study.  Multiple statistical challenges arose in this effort, leading to the development of  the "stratified micro-randomized trial'' design.  In these designs, each individual is randomized to treatment repeatedly at times determined by predictions of risk.  These "risk" times may be impacted by prior treatment. I will describe the statistical challenges and detail how they can be met. 

PDF iconWalter Dempsey - flyer.pdf