summary.AROC: Summary method for 'AROC' objects

In AROC: Covariate-Adjusted Receiver Operating Characteristic Curve Inference

Summary method for AROC objects

Description

Default summary method for objects fitted with AROC.bnp(), AROC.bsp(), AROC.sp(), AROC.kernel(), pooledROC.BB() or pooledROC.emp() functions.

Usage

## S3 method for class 'AROC'
summary(object, ...)

Arguments

object	an object of class AROC as produced by AROC.bnp(), AROC.bsp(), AROC.sp(), AROC.kernel(), pooledROC.BB() or pooledROC.emp()
...	Further arguments passed to or from other methods. Not yet implemented.

Details

A short summary is printed including the area under the covariate-adjusted ROC curve (AAUC) or the area under the pooled ROC curve (AUC), and if required, the partial area under the covariate-adjusted ROC curve (pAAUC). For the Bayesian methods, and if required, the function also provides the log pseudo marginal likelihood (LPML) and/or widely applicable information criterion (WAIC).

See Also

AROC.bnp, AROC.bsp, AROC.sp, AROC.kernel, pooledROC.BB or pooledROC.emp.

Examples

library(AROC)
data(psa)
# Select the last measurement
newpsa <- psa[!duplicated(psa$id, fromLast = TRUE),]

# Log-transform the biomarker
newpsa$l_marker1 <- log(newpsa$marker1)

m0 <- AROC.bnp(formula.healthy = l_marker1 ~ f(age, K = 0),
group = "status", tag.healthy = 0, data = newpsa, scale = TRUE,
p = seq(0,1,l=101), compute.lpml = TRUE, compute.WAIC = TRUE,
a = 2, b = 0.5, L = 10, nsim = 5000, nburn = 1000)

summary(m0)

AROC documentation built on March 18, 2022, 5:22 p.m.