compute.threshold.pooledROC.BB: Pooled ROC-based threshold values.

Description

Estimates pooled ROC-based threshold values using the Bayesian bootstrap estimator proposed by Gu et al. (2008).

Usage

compute.threshold.pooledROC.BB(object, FPF = 0.5)

Arguments

object

An object of class AROC as produced by pooledROC.BB.

FPF

Numeric vector with the FPF at which to calculate the pooled ROC-based threshold values. Atomic values are also valid.

Value

As a result, the function provides a list with the following components:

thresholds

A matrix with the posterior mean and posterior 2.5% and 97.5% quantiles of the pooled ROC-based threshold values. The matrix has as many rows as different FPFs.

FPF

the supplied FPF argument

TPF

TPFs corresponding to the estimated threshold. In addition to the posterior mean, the 95% pointwise credible band is also returned.

References

Gu, J., Ghosal, S., and Roy, A. (2008). Bayesian bootstrap estimation of ROC curve. Statistics in Medicine, 27, 5407--5420.

Examples

Run this code

# NOT RUN {
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)
# }
# NOT RUN {
m0_BB <- pooledROC.BB(y0 = newpsa$l_marker1[newpsa$status == 0], 
            y1 = newpsa$l_marker1[newpsa$status == 1], p = seq(0,1,l=101), B = 5000)

### Threshold values for a fixed FPF
th_m0_BB <- compute.threshold.pooledROC.BB(m0_BB, FPF = 0.1)

th_m0_BB$threshold
# }