Re: [R] the standard error of the quantile

Then see the latter part of my note. I think also that, at least for the median, the survival package will compute it more quickly for inclusion in a bootstrap loop. Note that you forgot to state require(survival) or library(survival) below. Frank swatch110362 wrote: > > Thanks for your help.

Re: [R] the standard error of the quantile

Thanks for your help. But I need to estimator the standard error of the quantile in "survival analysis", because my data is censored. For example~ T<-c(84,240,261,332,348,437,521,565) S<-c(0,1,1,0,1,0,1,0) ##0 for censoed; 1 for event G<-rep(1,8) ori_s.surv<-survfit(Surv(T,S)~G) -- View this

Re: [R] the standard error of the quantile

In small to moderate sample sizes, the Harrell-Davis quantile estimator is more accurate than the ordinary sample quantile, and there is a good standard error estimator for it using U-statistics. See the hdquantile function in the Hmisc package. Frank swatch110362 wrote: > > hi~ > I need to esti