Explained Variation in Correlated Survival Data
Presented by Ronghui (Lily) Xu, UCSD/ Biostatistics and Bioinformatics
Thursday, July 23, 2015
Time: 10:30 AM – 12:00 PM Pacific / 1:30 PM – 3:00 PM Eastern
Host Location: Santa Monica, conference room 1226
Other Locations: Pittsburgh (room 6207a) & Washington, DC (room 4132)
Explained variation in survival data has attracted much attention in recent years. In this talk, we consider explained variation in correlated survival data, specifically under the proportional hazards mixed-effects modeling (PHMM) of such data, which provides a natural setting for the decomposition of different sources of variation. A motivation of the concept originated from genetic epidemiology. More generally, explained variation can be formulated in different ways, and we discuss the formulations that are often encountered in the literature and that are interpretable in practice. We study the proposed measures both in theory and through simulation, and discuss some common pitfalls in using and understanding such measures in practice. To conclude, we show some interesting applications to both multi-center clinical trials and recurrent events.
About the Presenter
Ronghui (Lily) Xu is Professor of Biostatistics and Bioinformatics at the University of California, San Diego. Her main research areas include survival analysis and random effects models. Dr. Xu received both her Masters in Applied Mathematics (1995) and her Ph.D. (1996) from UCSD. She worked for one year as a graduate researcher at the UCSD Cancer Center and the Department of Mathematics before taking up an Assistant Professorship in 1997 in the Department of Biostatistics, Harvard School of Public Health and the Department of Biostatistical Science, Dana-Farber Cancer Institute in Boston, MA. She returned to UCSD in 2004 as an Associate Professor with the Department of Family and Preventive Medicine and the Department of Mathematics.
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Sponsored by the RAND Statistics Group