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# last modified 2015-02-03 by J. Fox
# quantile.survfit <-
# function(x, quantiles=c(.25, .5, .75), ...){
# quants <- function(surv, lower, upper, t){
# if (length(surv) == 1) return(NA)
# warn <- options(warn=-1)
# on.exit(options(warn))
# select <- sapply(quantiles, function(q) q >= surv)
# posn <- apply(select, 2, function(x) min(which(x)))
# q <- t[posn]
# select <- sapply(quantiles, function(q) q >= lower)
# posn <- apply(select, 2, function(x) min(which(x)))
# low <- t[posn]
# select <- sapply(quantiles, function(q) q >= upper)
# posn <- apply(select, 2, function(x) min(which(x)))
# up <- t[posn]
# rbind(low, q, up)
# }
# summary <- summary(x)
# conf.level <- x$conf.int
# strata <- summary$strata
# if (is.null(strata)) {
# table <- quants(summary$surv, summary$lower, summary$upper, summary$time)
# dimnames(table) <- list(Estimate=c(paste("lower", conf.level, "CL"), "quantile", paste("upper", conf.level, "CL")),
# "Survival Probability"=as.character(round(quantiles, 3)))
# } else {
# levels <- levels(strata)
# table <- array(0, c(3, length(quantiles), length(levels)))
# dimnames(table) <- list(Estimate=c(paste("lower", conf.level, "CL"), "quantile", paste("upper", conf.level, "CL")),
# "Survival Probability"=as.character(round(quantiles, 3)), Stratum=levels)
# for (s in levels){
# select <- strata == s
# table[, , s] <- quants(summary$surv[select], summary$lower[select],
# summary$upper[select], summary$time[select])
# }
# }
# table
# }
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