auc.nonpara.mw {CalibrationCurves} | R Documentation |
Obtain the point estimate and the confidence interval of the AUC by various methods based on the Mann-Whitney statistic.
auc.nonpara.mw(x, y, conf.level=0.95,
method=c("newcombe", "pepe", "delong",
"jackknife", "bootstrapP", "bootstrapBCa"),
nboot)
x |
a vector of observations from class P. |
y |
a vector of observations from class N. |
conf.level |
confidence level of the interval. The default is 0.95. |
method |
a method used to construct the CI. |
nboot |
number of bootstrap iterations. |
The function implements various methods based on the Mann-Whitney statistic.
Point estimate and lower and upper bounds of the CI of the AUC.
The observations from class P tend to have larger values than that from class N.
This help-file is a copy of the original help-file of the function auc.nonpara.mw
from the auRoc-package. It is important to note
that, when using method="pepe"
, the confidence interval is computed as documented in Qin and Hotilovac (2008) and that this is
different from the original function.
Elizabeth R Delong, David M Delong, and Daniel L Clarke-Pearson (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44 837-845
Dai Feng, Giuliana Cortese, and Richard Baumgartner (2015) A comparison of confidence/credible interval methods for the area under the ROC curve for continuous diagnostic tests with small sample size. Statistical Methods in Medical Research DOI: 10.1177/0962280215602040
Robert G Newcombe (2006) Confidence intervals for an effect size measure based on the Mann-Whitney statistic. Part 2: asymptotic methods and evaluation. Statistics in medicine 25(4) 559-573
Margaret Sullivan Pepe (2003) The statistical evaluation of medical tests for classification and prediction. Oxford University Press
Qin, G., & Hotilovac, L. (2008). Comparison of non-parametric confidence intervals for the area under the ROC curve of a continuous-scale diagnostic test. Statistical Methods in Medical Research, 17(2), pp. 207-21