| tidy.survfit {broom} | R Documentation |
Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies cross models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.
## S3 method for class 'survfit' tidy(x, ...)
x |
An |
... |
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
A tibble::tibble with one row for each time point and columns:
time |
timepoint |
n.risk |
number of subjects at risk at time t0 |
n.event |
number of events at time t |
n.censor |
number of censored events |
estimate |
estimate of survival or cumulative incidence rate when multistate |
std.error |
standard error of estimate |
conf.high |
upper end of confidence interval |
conf.low |
lower end of confidence interval |
state |
state if multistate survfit object inputted |
strata |
strata if stratified survfit object inputted |
Other survival tidiers:
augment.coxph(),
augment.survreg(),
glance.aareg(),
glance.cch(),
glance.coxph(),
glance.pyears(),
glance.survdiff(),
glance.survexp(),
glance.survfit(),
glance.survreg(),
tidy.aareg(),
tidy.cch(),
tidy.coxph(),
tidy.pyears(),
tidy.survdiff(),
tidy.survexp(),
tidy.survreg()
library(survival)
cfit <- coxph(Surv(time, status) ~ age + sex, lung)
sfit <- survfit(cfit)
tidy(sfit)
glance(sfit)
library(ggplot2)
ggplot(tidy(sfit), aes(time, estimate)) + geom_line() +
geom_ribbon(aes(ymin=conf.low, ymax=conf.high), alpha=.25)
# multi-state
fitCI <- survfit(Surv(stop, status * as.numeric(event), type = "mstate") ~ 1,
data = mgus1, subset = (start == 0))
td_multi <- tidy(fitCI)
td_multi
ggplot(td_multi, aes(time, estimate, group = state)) +
geom_line(aes(color = state)) +
geom_ribbon(aes(ymin = conf.low, ymax = conf.high), alpha = .25)