cc.ROC {pwrFDR}

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

es.ROC

Examples

    cc.ROC(FPR0=0.15, TPR0=0.80, TPR1=0.90)