Document Type
Article
Department/Program
Mathematics
Journal Title
IEEE Transactions on Reliability
Pub Date
6-2008
Volume
57
Issue
2
First Page
248
Abstract
Simultaneous discrimination among various parametric lifetime models is an important step in the parametric analysis of survival data. We consider a plot of the skewness versus the coefficient of variation for the purpose of discriminating among parametric survival models. We extend the method of Cox & Oakes from complete to censored data by developing an algorithm based on a competing risks model and kernel function estimation. A by-product of this algorithm is a nonparametric survival function estimate.
Recommended Citation
Leemis, Lawrence and Block, A. D., Parametric Model Discrimination for Heavily Censored Survival Data (2008). IEEE Transactions on Reliability, 57(2), 248-259.
https://doi.org/10.1109/TR.2008.923488
DOI
https://doi.org/10.1109/TR.2008.923488
