pooledROC.BB {AROC} | R Documentation |
Bayesian bootstrap estimation of the pooled ROC curve.
Description
Estimates the pooled ROC curve using the Bayesian bootstrap estimator proposed by Gu et al. (2008).
Usage
pooledROC.BB(y0, y1, p = seq(0, 1, l = 101), B = 5000)
Arguments
y0 |
Diagnostic test outcomes in the healthy group. |
y1 |
Diagnostic test outcomes in the diseased group. |
p |
Set of false positive fractions (FPF) at which to estimate the covariate-adjusted ROC curve. |
B |
An integer value specifying the number of Bayesian bootstrap resamples. By default 5000. |
Value
As a result, the function provides a list with the following components:
call |
the matched call. |
p |
Set of false positive fractions (FPF) at which the pooled ROC curve has been estimated |
ROC |
Estimated pooled ROC curve, and corresponding 95% credible intervals |
AUC |
Estimated pooled AUC, and corresponding 95% credible intervals. |
References
Gu, J., Ghosal, S., and Roy, A. (2008). Bayesian bootstrap estimation of ROC curve. Statistics in Medicine, 27(26), 5407 - 5420.
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$marker1)
m0_BB <- pooledROC.BB(newpsa$l_marker1[newpsa$status == 0],
newpsa$l_marker1[newpsa$status == 1], p = seq(0,1,l=101), B = 5000)
summary(m0_BB)
plot(m0_BB)