Statistics Seminar: K.B. Kulasekera (University of Louisville) -- Personalized Plans with Multiple Treatments

Abstract

Designing optimal treatment regimes based on individual patient characteristics 
has gained momentum over the last few years. Dynamic treatment regimes that are 
geared towards the ``best" outcome for a patient based on his/her genetic and 
genomic markers are of high importance. In this work we propose a method for 
treatment assignment based on individual covariate information for a patient. 
While most techniques found in the literature can only handle the assignment of 
two treatments, our method covers more than two treatments and it can be applied 
with a broad set of models. Furthermore, it has desirable large sample properties. 

An empirical study using simulations and a real data analysis show the 
applicability of the proposed procedure