Journal
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
Volume 87, Issue 2, Pages 132-137Publisher
ELSEVIER IRELAND LTD
DOI: 10.1016/j.cmpb.2007.05.009
Keywords
predictive accuracy; survival analysis; Cox model; parametric models; Bayesian model averaging; R; S-PLUS
Ask authors/readers for more resources
When the purpose of a survival regression model is to predict future outcomes, the predictive accuracy of the model needs to be evaluated before practical application. Various measures of predictive accuracy have been proposed for survival data, none of which has been adopted as a standard, and their inclusion in statistical software is disregarded. We developed the SUREV library for R and S-PLUS, which includes functions for evaluating the predictive accuracy measures proposed by Schemper and Henderson. The library evaluates the predictive accuracy of parametric regression models and of Cox models. The predictive accuracy of the Cox model can be obtained also when time-dependent covariates are included because of non-proportional hazards or when using Bayesian model averaging. The use of the library is illustrated with examples based on a real data set. (c) 2007 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available