K.C.S.Pillai Memorial Lecture

Individualizing Dynamic Treatments: Statistical Challenges and Some Solutions

Susan Murphy
University of Michigan

Start Date and Time: Thu, 22 Apr 2010, 4:30 PM

End Date and Time: Thu, 22 Apr 2010, 5:30 PM

Venue: MATH 175

Refreshments: Refreshments will be served at 4:00 PM in HAAS 111.


An emerging and exciting area of clinical science involves the use of data to directly inform the tactics and strategies used to provide treatment in clinical practice. Clinical practice involves the use of dynamic information on patients to individualize treatment, that is, clinical practice requires sequential decision making. To a large extent, the development of methods to inform sequential decision making has occurred outside of statistics (computer science, operations research, engineering). However the developed methods are primarily algorithmic; these methods either do not provide inferential tools, or at best, provide ad hoc inferential tools.

This talk will survey the statistical challenges inherent in using data to inform sequential data making and provide some first solutions.

Last Updated: Aug 31, 2017 11:20 AM

Purdue Department of Statistics, 250 N. University St, West Lafayette, IN 47907

Phone: (765) 494-6030, Fax: (765) 494-0558

© 2015 Purdue University | An equal access/equal opportunity university | Copyright Complaints

Trouble with this page? Disability-related accessibility issue? Please contact the College of Science Webmaster.