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.