tidy.survexp: Tidy a(n) survexp object

View source: R/survival-survexp-tidiers.R

tidy.survexpR Documentation

Tidy a(n) survexp object


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 class 'survexp'
tidy(x, ...)



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


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. Two exceptions here are:

  • tidy() methods will warn when supplied an exponentiate argument if it will be ignored.

  • augment() methods will warn when supplied a newdata argument if it will be ignored.


A tibble::tibble() with columns:


Number of individuals at risk at time zero.


Point in time.


Estimate survival

See Also

tidy(), survival::survexp()

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()


# load libraries for models and data

# fit model
sexpfit <- survexp(
  futime ~ 1,
  rmap = list(
    sex = "male",
    year = accept.dt,
    age = (accept.dt - birth.dt)
  method = "conditional",
  data = jasa

# summarize model fit with tidiers

broom documentation built on Aug. 30, 2022, 1:07 a.m.