Try using psurvreg(x, mean=fit2$coef, scale=fit2$scale, dist='extreme') The psurvreg and qsurvreg functions inherit the same parameterizations as survreg. I have trouble myself matching the location/scale form of survreg to default parameterizations used in the weibull, extreme, etc distributions.
For a multivariate model the call above would use mean = sum(x* fit$coef), where "x" was the vector of values for a hypothetical subject. An alternative is to use predict(fit2, type='quantile'), there is an example in help(predict.survreg). Terry Therneau PS Your title was wrong, the quesion is about survreg not coxph. Also note that the Gomperz and extreme value distributions are not exactly the same: the Gompertz adds the restriction that x>0. This changes the normalization constant, but if most of the data is far from zero the difference is very small. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
