Smoothing in the Analysis of Survival Time Data
Kenneth R. Hess, PhD
Professor
Department of Biostatistics
University of Texas M. D. Anderson Cancer Center
We will discuss the use of kernel-based smoothing methods in estimation of the density function, the hazard function and the survival function. We will also discuss estimating functions of the survival time distribution (quantiles and probabilities) as smooth functions of numeric covariates. These methods are useful adjuncts in the analysis of survival time data and work in the presence of right censoring – which occurs when not all patients in a cohort have died at the time of the data analysis. Emphasis will be on real examples and R software for producing the estimates.
HACASA meetings are open to the public! Please pass on copies of this announcement to colleagues and friends and post on appropriate bulletin boards.
WHEN and WHERE: *Tuesday, September 16, 2014* at Duncan Hall, Rice University
5:30pm - Social Time and with snacks & drinks: Room 3076
6:30pm – Talk (Room 3076)
Duncan Hall (also known as the Computational Engineering Building) is on the northeast side of the Rice University Campus. For parking information and directions please refer to the Rice parking websites, the following have been found helpful:
http://cohesion.rice.edu/campusservices/parktrans/parking/visitors.cfm
http://www.rice.edu/maps/maps.html