Biostatistics Weekly Seminar


Methods for evaluating the time-varying prognostic performance of survival models

C. Jason Liang, PhD
National Institute of Allergery and Infectious Diseases, NIH

Many prognostic models are created using survival data. In practice, the development of such models remains fairly ad hoc, and the temporal aspect of survival data is often underused. I will outline a number of existing methods for evaluating prognostic survival models. In particular, the emphasis will be on tools that can quantify how prognostic performance varies with time. I will also present a complementary new tool we have developed, the hazard discrimination summary (HDS). HDS is an interpretable, risk-based measure of how a modelís discrimination varies with time. I will also describe a connection between HDS and the Cox model partial likelihood.


MRBIII, Room 1220
25 September 2019
1:30pm


Speaker Itinerary

Topic revision: r3 - 13 Sep 2019, AndrewSpieker
 

This site is powered by FoswikiCopyright © 2013-2017 by the contributing authors. All material on this collaboration platform is the property of the contributing authors.
Ideas, requests, problems regarding Vanderbilt Biostatistics Wiki? Send feedback