tidy.cch {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 '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 one row for each term in the
regression. The tibble has columns:
term |
The name of the regression term. |
estimate |
The estimated value of the regression term. |
std.error |
The standard error of the regression term. |
statistic |
The value of a statistic, almost always a T-statistic, to use in a hypothesis that the regression term is non-zero. |
p.value |
The two-sided p-value associated with the observed statistic. |
conf.low |
The low end of a confidence interval for the regression
term. Included only if |
conf.high |
The high end of a confidence interval for the regression
term. Included only if |
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
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)