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.
# S3 method for survexp tidy(x, ...)
x | An |
---|---|
... | Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
Other survexp tidiers:
glance.survexp()
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.survfit()
,
tidy.survreg()
A tibble::tibble()
with columns:
Number of individuals at risk at time zero.
Point in time.
Estimate survival
if (requireNamespace("survival", quietly = TRUE)) { library(survival) sexpfit <- survexp( futime ~ 1, rmap = list( sex = "male", year = accept.dt, age = (accept.dt - birth.dt) ), method = "conditional", data = jasa ) tidy(sexpfit) glance(sexpfit) } #> # A tibble: 1 × 3 #> n.max n.start timepoints #> <int> <int> <int> #> 1 102 102 88