get_confint {shinyCox}

Get confidence intervals for predicted survival curves

Description

Creates confidence levels for plotting predicted survival curves.

Usage

get_confint(p, se, conf.type, conf.int, ulimit = TRUE)

Arguments

p

Vector of survival probabilities

se

Vector of standard errors

conf.type

Type of confidence interval, includes 'plain', 'log', 'log-log', 'logit', and 'arcsin'.

conf.int

The level for two-sided confidence interval on the predicted survival curve, default is 0.95.

ulimit

Should upper bound be limited to 1, default is 'TRUE'

Value

list of length two, containing the lower and upper confidence levels

Examples

library(survival)
library(shinyCox)
colondeaths <- colon[colon$etype == 2, ]
split_colon <- split(colondeaths, colondeaths$rx)

colon_arm1 <- split_colon$Obs
colon1ph <- coxph(Surv(time, status) ~ factor(extent) + nodes + strata(surg)
                  + factor(differ),
                  colon_arm1,
                  x = TRUE, model = TRUE)

new.data = cbind.data.frame(`factor(extent)` = 3,
                         `surg` = "surg=0",`factor(differ)` = 2,`nodes` = 5)


coxfit = prep_coxfit(colon1ph)
coxlist = surv_pred_info(colon1ph)

for_ci = predict_se(coxlist, coxfit, new.data)

get_confint(for_ci$surv, for_ci$std.err, conf.int = 0.95,
            conf.type = "log-log")