compute.threshold.pooledROC.BB {AROC} | R Documentation |
Estimates pooled ROC-based threshold values using the Bayesian bootstrap estimator proposed by Gu et al. (2008).
compute.threshold.pooledROC.BB(object, FPF = 0.5)
object |
An object of class |
FPF |
Numeric vector with the FPF at which to calculate the pooled ROC-based threshold values. Atomic values are also valid. |
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. |
Gu, J., Ghosal, S., and Roy, A. (2008). Bayesian bootstrap estimation of ROC curve. Statistics in Medicine, 27, 5407–5420.
library(AROC) data(psa) # Select the last measurement newpsa <- psa[!duplicated(psa$id, fromLast = TRUE),] # Log-transform the biomarker newpsa$l_marker1 <- log(newpsa$marker1) m0_BB <- pooledROC.BB(y0 = newpsa$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