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## Do the test on the simple agreg data set#fit <-coxph(Surv(start, stop, event)~ x, test2, method='breslow')fitfit0 <-coxph(Surv(start, stop, event)~ x, test2, iter=0)fit0$coefcoxph(Surv(start, stop, event)~ x, test2, iter=1, method='breslow')$coefcoxph(Surv(start, stop, event)~ x, test2, iter=2, method='breslow')$coefcoxph(Surv(start, stop, event)~ x, test2, iter=3, method='breslow')$coefcoxph(Surv(start, stop, event) ~ x, test2, method='efron')coxph(Surv(start, stop, event) ~ x, test2, method='exact')resid(fit0)resid(fit0, 'scor')resid(fit0, 'scho')resid(fit)resid(fit, 'scor')resid(fit, 'scho')resid(coxph(Surv(start, stop, event)~ x, test2, iter=0, init=log(2)), 'score')sfit <-survfit(fit)sfitsummary(sfit)# make a doubled data settemp <- rbind(test2, test2)temp <- data.frame(temp, x2=c(test2$x, test2$x^2),ss=c(rep(0, nrow(test2)), rep(1, nrow(test2))))fitx <- coxph(Surv(start, stop, event) ~ x2 * strata(ss), data=temp,method='breslow')sfit <- survfit(fitx, c(fitx$means[1], 0) )sfitsummary(sfit)## Even though everyone in strata 1 has x2==0, I won't get the same survival# curve above if survfit is called without forcing predicted x2 to be# zero-- otherwise I am asking for a different baseline than the# simple model did. In this particular case coef[2] is nearly zero, so# the curves are the same, but the variances differ.## This mimics 'byhand3' and the documentationfit <- coxph(Surv(start, stop, event) ~x, test2, method='breslow')tdata <- data.frame( start=c(0,20, 6,0,5),stop =c(5,23,10,5,15),event=rep(0,5),x=c(0,0,1,0,2) )temp <- survfit(fit, tdata, individual=T)temp2 <- byhand3(fit$coef)all.equal(temp$surv, temp2$surv)all.equal(temp2$std, temp$std.err)temp2