| tidy.crr | 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 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 'crr'
tidy(x, exponentiate = FALSE, conf.int = FALSE, conf.level = 0.95, ...)
| x | A  | 
| exponentiate | Logical indicating whether or not to exponentiate the
the coefficient estimates. This is typical for logistic and multinomial
regressions, but a bad idea if there is no log or logit link. Defaults
to  | 
| conf.int | Logical indicating whether or not to include a confidence
interval in the tidied output. Defaults to  | 
| conf.level | The confidence level to use for the confidence interval
if  | 
| ... | 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. | 
tidy(), cmprsk::crr()
Other cmprsk tidiers: 
glance.crr()
library(cmprsk)
# time to loco-regional failure (lrf)
lrf_time <- rexp(100)
lrf_event <- sample(0:2, 100, replace = TRUE)
trt <- sample(0:1, 100, replace = TRUE)
strt <- sample(1:2, 100, replace = TRUE)
# fit model
x <- crr(lrf_time, lrf_event, cbind(trt, strt))
# summarize model fit with tidiers
tidy(x, conf.int = TRUE)
glance(x)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.