COMPARISON OF MEDIAN SURVIVAL TIMES WITH ADJUSTMENT FOR COVARIATES

Authors
Citation
T. Karrison, COMPARISON OF MEDIAN SURVIVAL TIMES WITH ADJUSTMENT FOR COVARIATES, Statistics in medicine, 14(23), 1995, pp. 2537-2553
Citations number
26
Categorie Soggetti
Statistic & Probability","Medicine, Research & Experimental","Public, Environmental & Occupation Heath","Statistic & Probability
Journal title
ISSN journal
02776715
Volume
14
Issue
23
Year of publication
1995
Pages
2537 - 2553
Database
ISI
SICI code
0277-6715(1995)14:23<2537:COMSTW>2.0.ZU;2-S
Abstract
Brookmeyer and Crowley derived a non-parametric confidence interval fo r the median survival time of a homogeneous population by inverting a generalization of the sign test for censored data. The 1-alpha confide nce interval for the median is essentially the set of all values t suc h that the Kaplan-Meier estimate of the survival curve at time t does not differ significantly from one-half at the two-sided alpha level. S u and Wei extended this approach to the two-sample problem and derived a confidence interval for the difference in median survival times bas ed on the Kaplan-Meier estimates of the individual survival curves and a 'minimum dispersion' test statistic. Here, I incorporate covariates into the analysis by assuming a proportional hazards model for the co variate effects, while leaving the two underlying survival curves virt ually unconstrained. I generate a simultaneous confidence region for t he two median survival times, adjusted to any selected value, z, of th e covariate vector using a test-based approach analogous to Brookmeyer and Crowley's for the one-sample case. This region is, in turn, used to derive a confidence interval for the difference in median survival times between the two treatment groups at the selected value of z. Emp loyment of a procedure suggested by Aitchison sets the level of the si multaneous region to a value that should yield, at least approximately , the desired confidence coefficient for the difference in medians. Si mulation studies indicate that the method provides reasonably accurate coverage probabilities.