broom (version 0.8.0)

tidy.survdiff: Tidy a(n) survdiff object

Description

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 across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.

Usage

# S3 method for survdiff
tidy(x, ...)

Arguments

x

An survdiff object returned from survival::survdiff().

...

Additional arguments. Not used. Needed to match generic signature only. Cautionary note: Misspelled arguments will be absorbed in ..., where they will be ignored. If the misspelled argument has a default value, the default value will be used. For example, if you pass conf.lvel = 0.9, all computation will proceed using conf.level = 0.95. Additionally, if you pass newdata = my_tibble to an augment() method that does not accept a newdata argument, it will use the default value for the data argument.

Value

A tibble::tibble() with columns:

exp

Weighted expected number of events in each group.

N

Number of subjects in each group.

obs

weighted observed number of events in each group.

See Also

tidy(), survival::survdiff()

Other survdiff tidiers: glance.survdiff()

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.survexp(), tidy.survfit(), tidy.survreg()

Examples

# NOT RUN {

# feel free to ignore the following line<U+2014>it allows {broom} to supply 
# examples without requiring the model-supplying package to be installed.
if (requireNamespace("survival", quietly = TRUE)) {

# load libraries for models and data
library(survival)

# fit model
s <- survdiff(
  Surv(time, status) ~ pat.karno + strata(inst),
  data = lung
)

# summarize model fit with tidiers
tidy(s)
glance(s)

}

# }