summary.pooledROC: Summary method for 'pooledROC' objects

In ROCnReg: ROC Curve Inference with and without Covariates

Summary method for pooledROC objects

Description

Default summary method for objects fitted with pooledROC.BB, pooledROC.emp, pooledROC.kernel, or pooledROC.dpm functions.

Usage

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

Arguments

object	An object of class pooledROC as produced by pooledROC.BB, pooledROC.emp, pooledROC.kernel, or pooledROC.dpm.
...	Further arguments passed to or from other methods. Not yet implemented.

Details

A short summary is printed including the call to the function, the method, samples sizes, the area under the pooled ROC curve (AUC), and if required, the partial area under the pooled ROC curve. For the nonparametric Bayesian approach (pooledROC.dpm()), and if required, the function provides the log pseudo marginal likelihood (LPML), the widely applicable information criterion (WAIC) and/or the deviance information criterion (DIC). For the kernel-based approach (pooledROC.dpm()), information regarding the selected bandwidths and the density bandwidth selection method is presented.

See Also

pooledROC.BB, pooledROC.emp, pooledROC.kernel or pooledROC.dpm.

Examples

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

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

m0_emp <- pooledROC.emp(marker = "l_marker1", group = "status",
            tag.h = 0, data = newpsa, p = seq(0,1,l=101), B = 500)

summary(m0_emp)

plot(m0_emp)

ROCnReg documentation built on March 31, 2023, 5:42 p.m.