Ch21-cc-ROC: Computes the optimal number of controls per case in...
In pwrFDR: FDR Power
Description
Usage
Arguments
Value
Author(s)
References
See Also
Examples
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
1
2
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
1
cc.ROC(FPR0=0.15, TPR0=0.80, TPR1=0.90)
pwrFDR documentation built on May 12, 2021, 5:07 p.m.
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Description Usage Arguments Value Author(s) References See Also Examples
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
1 2 |
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
1 | cc.ROC(FPR0=0.15, TPR0=0.80, TPR1=0.90)
|
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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