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)