| tidy.pyears {broom} | R Documentation |
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 class 'pyears' tidy(x, ...)
x |
A |
... |
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
A tibble::tibble with one row for each time point and columns:
pyears |
person-years of exposure |
n |
number of subjects contributing time |
event |
observed number of events |
expected |
expected number of events (present only if a
|
If the data.frame = TRUE argument is supplied to pyears,
this is simply the contents of x$data.
Other pyears tidiers:
glance.pyears()
Other survival tidiers:
augment.coxph(),
augment.survreg(),
glance.aareg(),
glance.cch(),
glance.coxph(),
glance.pyears(),
glance.survdiff(),
glance.survexp(),
glance.survfit(),
glance.survreg(),
tidy.aareg(),
tidy.cch(),
tidy.coxph(),
tidy.survdiff(),
tidy.survexp(),
tidy.survfit(),
tidy.survreg()
library(survival)
temp.yr <- tcut(mgus$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)
tidy(pfit)
glance(pfit)
# 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)
tidy(pfit2)
glance(pfit2)