pooledROC.BB | R Documentation |
Estimates the pooled ROC curve using the Bayesian bootstrap estimator proposed by Gu et al. (2008).
pooledROC.BB(y0, y1, p = seq(0, 1, l = 101), B = 5000)
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. |
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. |
Gu, J., Ghosal, S., and Roy, A. (2008). Bayesian bootstrap estimation of ROC curve. Statistics in Medicine, 27(26), 5407 - 5420.
AROC.bnp
, AROC.bsp
, AROC.sp
, AROC.kernel
, pooledROC.BB
or pooledROC.emp
.
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)
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