tidy.pyears: Tidy a(n) pyears object

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

tidy.pyearsR Documentation

Tidy a(n) pyears 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 'pyears'
tidy(x, ...)



A pyears object returned from survival::pyears().


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.


expected is only present in the output when if a ratetable term is present.

If the data.frame = TRUE argument is supplied to pyears, this is simply the contents of x$data.


A tibble::tibble() with columns:


Expected number of events.


Person-years of exposure.


number of subjects contributing time


observed number of events

See Also

tidy(), survival::pyears()

Other pyears tidiers: glance.pyears()

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


# load libraries for models and data

# generate and format data
temp.yr <- tcut(mgus$dxyr, 55:92, labels = as.character(55:91))
temp.age <- tcut(mgus$age, 34:101, labels = as.character(34:100))
ptime <- ifelse(is.na(mgus$pctime), mgus$futime, mgus$pctime)
pstat <- ifelse(is.na(mgus$pctime), 0, 1)
pfit <- pyears(Surv(ptime / 365.25, pstat) ~ temp.yr + temp.age + sex, mgus,
  data.frame = TRUE

# summarize model fit with tidiers

# if data.frame argument is not given, different information is present in
# output
pfit2 <- pyears(Surv(ptime / 365.25, pstat) ~ temp.yr + temp.age + sex, mgus)


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