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, ...)
x |
An |
conf.level |
confidence level for CI |
... |
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
A tibble::tibble() with columns:
conf.high |
Upper bound on the confidence interval for the estimate. |
conf.low |
Lower bound on the confidence interval for the estimate. |
estimate |
The estimated value of the regression term. |
p.value |
The two-sided p-value associated with the observed statistic. |
statistic |
The value of a T-statistic to use in a hypothesis that the regression term is non-zero. |
std.error |
The standard error of the regression term. |
term |
The name of the regression term. |
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()
if (requireNamespace("survival", quietly = TRUE)) {
library(survival)
# 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.ccP <- cch(Surv(edrel, rel) ~ stage + histol + age,
data = ccoh.data,
subcoh = ~subcohort, id = ~seqno, cohort.size = 4028
)
tidy(fit.ccP)
# coefficient plot
library(ggplot2)
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)
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