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 survdiff
tidy(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.
A tibble::tibble with one row for each time point and columns:
The initial columns correspond to the grouping factors on the right hand side of the model formula.
weighted observed number of events in each group
weighted expected number of events in each group
number of subjects in each group
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
# NOT RUN {
library(survival)
s <- survdiff(
Surv(time, status) ~ pat.karno + strata(inst),
data = lung
)
tidy(s)
glance(s)
# }
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