cc.ROC {pwrFDR} | R Documentation |
Computes the optimal number of controls per case in hypothesis tests
involving the ROC. Included here with the intent that it can be
used in conjunction with pwrFDR
to allow power/sample
size calculation for multiple tests of ROC curve based hypothesis.
See details.
Description
In hypothesis tests of TPR_1 vs TPR_0 at fixed FPR, or
FPR_1 vs FPR_0 at fixed TPR, this computes the optimal number
of controls per case. Required by es.ROC
Usage
cc.ROC(FPR0, FPR1 = NULL, TPR0, TPR1 = NULL, b = NULL)
Arguments
FPR0 |
When the TPR is fixed, the FPR under the null. Otherwise the fixed FPR. |
FPR1 |
When the TPR is fixed, the FPR under the alternative. Otherwise left blank. |
TPR0 |
When the FPR is fixed, the TPR under the null. Otherwise the fixed TPR. |
TPR1 |
When the FPR is fixed, the TPR under the alternative. Otherwise left blank. |
b |
Nominal slope of the ROC at FPR0. Taken to be 1 by default. |
Value
The optimal number of controls per case.
Author(s)
Grant Izmirlian <izmirlian at nih dot gov>
References
Pepe M. S., Feng Z, Janes, H Bossuyt P. M. and Potter J. D. Pivotal evaluation of the accuracy of a biomarker used for classification or prediction. Supplement. J Natl Cancer Inst 2008;100: 1432–1438
See Also
Examples
cc.ROC(FPR0=0.15, TPR0=0.80, TPR1=0.90)