CstatCI: Confidence Intervals for the C Statistic (AUC)

In DescTools: Tools for Descriptive Statistics

Confidence Intervals for the C Statistic (AUC)

Description

Calculate bootstrap intervals for the C statistic (Area under the curve AUC), based on a glm.

Usage

CstatCI(
  object,
  conf.level = 0.95,
  sides = c("two.sided", "left", "right"),
  ...
)

Arguments

object	the model object as returned by glm.
conf.level	confidence level of the interval.
sides	a character string specifying the side of the confidence interval, must be one of "two.sided" (default), "left" or "right". "left" would be analogue to a hypothesis of "greater" in a t.test. You can specify just the initial letter.
...	further arguments are passed to the boot function. Supported arguments are type ("norm", "basic", "stud", "perc", "bca"), parallel and the number of bootstrap replicates R. If not defined those will be set to their defaults, being "basic" for type, option "boot.parallel" (and if that is not set, "no") for parallel and 999 for R.

Value

a numeric vector with 3 elements:

mean	mean
lwr.ci	lower bound of the confidence interval
upr.ci	upper bound of the confidence interval

Author(s)

Andri Signorell [e-mail]

See Also

BrierScore

Examples

utils::data(Pima.te, package = "MASS")
r.logit <- glm(type ~ ., data=Pima.te, family="binomial")

# calculate Brier score with confidence intervals
Cstat(r.logit)
CstatCI(r.logit, R=99)  # use higher R in real life!

DescTools documentation built on Sept. 26, 2024, 1:07 a.m.