tidy.cch: Tidy a(n) cch object

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

tidy.cchR Documentation

Tidy a(n) cch 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 'cch'
tidy(x, conf.level = 0.95, ...)



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


confidence level for CI


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:


Upper bound on the confidence interval for the estimate.


Lower bound on the confidence interval for the estimate.


The estimated value of the regression term.


The two-sided p-value associated with the observed statistic.


The value of a T-statistic to use in a hypothesis that the regression term is non-zero.


The standard error of the regression term.


The name of the regression term.

See Also

tidy(), survival::cch()

Other cch tidiers: glance.cch(), glance.survfit()

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


# load libraries for models and data

# examples come from cch documentation
subcoh <- nwtco$in.subcohort
selccoh <- with(nwtco, rel == 1 | subcoh == 1)
ccoh.data <- nwtco[selccoh, ]
ccoh.data$subcohort <- subcoh[selccoh]

# central-lab histology
ccoh.data$histol <- factor(ccoh.data$histol, labels = c("FH", "UH"))

# tumour stage
ccoh.data$stage <- factor(ccoh.data$stage, labels = c("I", "II", "III", "IV"))
ccoh.data$age <- ccoh.data$age / 12 # age in years

# fit model
fit.ccP <- cch(Surv(edrel, rel) ~ stage + histol + age,
  data = ccoh.data,
  subcoh = ~subcohort, id = ~seqno, cohort.size = 4028

# summarize model fit with tidiers + visualization

# coefficient plot

ggplot(tidy(fit.ccP), aes(x = estimate, y = term)) +
  geom_point() +
  geom_errorbarh(aes(xmin = conf.low, xmax = conf.high), height = 0) +
  geom_vline(xintercept = 0)

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