CompareAugAUCs: Inference on the Area Under the Cumulative Count Curve

In zrmacc/MCC: Functions for Comparing Mean Cumulative Count Curves

Inference on the Area Under the Cumulative Count Curve

Description

Confidence intervals and p-values for the difference and ratio of areas under the mean cumulative count curves, comparing treatment (arm = 1) with reference (arm = 0) with adjusted for covariates.

Usage

CompareAugAUCs(
  data,
  tau,
  alpha = 0.05,
  boot = FALSE,
  perm = FALSE,
  reps = 2000
)

Arguments

data	Formatted data frame. FormatData.
tau	Truncation time.
alpha	Alpha level.
boot	Logical, construct bootstrap confidence intervals?
perm	Logical, perform permutation test?
reps	Replicates for bootstrap/permutation inference.

Value

Object of class CompareAugAUCs with these slots:

• '@Areas': Marginal AUC for each arm.

• '@CIs': Observed difference and ratio in areas with confidence intervals.

• '@MCF': Mean cumulative count curve for each arm.

• '@Pvals': Bootstrap and permutation p-values.

• '@Reps': Bootstrap and permutation realizations of the test statistics.

Examples

# Simulate data set.
n <- 100
covariates <- data.frame(
  arm = c(rep(1, n/2), rep(0, n/2)),
  covar = rnorm(n)
)
data <- GenData(
  beta_event = c(log(0.5), 1),
  covariates = covariates
)

aucs <- CompareAUCs(
  data,
  covars = data$covar,
  tau = 2,
  boot = TRUE,
  perm = TRUE,
  reps = 25,
  alpha = 0.05
)
show(aucs)

zrmacc/MCC documentation built on July 16, 2025, 4:04 p.m.