es.ROC

In hypothesis tests of TPR_1 vs TPR_0 at fixed FPR, or
 FPR_1 vs FPR_0 at fixed TPR, this computes the
 equivalent Z-test effect size. This can then be passed
 the <code>effect.size</code> argument in a call to
 <code>pwrFDR</code> or <code>controlFDP</code>

Benjamini

Hochberg

microarrays

Multiple.Testing

average.power

k.power

lambda.power

Computing Average and TPX Power under various BHFDR type sequential
procedures. All of these procedures involve control of some summary of the
distribution of the FDP, e.g. the proportion of discoveries which are false
in a given experiment. The most widely known of these, the BH-FDR procedure,
controls the FDR which is the mean of the FDP. A lesser known procedure, due
to Lehmann and Romano, controls the FDX, or probability that the FDP exceeds
a user provided threshold. This is less conservative than FWE control
procedures but much more conservative than the BH-FDR proceudre. This
package and the references supporting it introduce a new procedure for
controlling the FDX which we call the BH-FDX procedure. This procedure
iteratively identifies, given alpha and lower threshold delta, an alpha*
less than alpha at which BH-FDR guarantees FDX control. This uses
asymptotic approximation and is only slightly more conservative than the
BH-FDR procedure. Likewise, we can think of the power in multiple testing
experiments in terms of a summary of the distribution of the True Positive
Proportion (TPP), the portion of tests truly non-null distributed that are
called significant. The package will compute power, sample size or any other
missing parameter required for power defined as (i) the mean of the TPP
(average power) or (ii) the probability that the TPP exceeds a given value,
lambda, (TPX power) via asymptotic approximation. All supplied theoretical
results are also obtainable via simulation. The suggested approach is to
narrow in on a design via the theoretical approaches and then make final
adjustments/verify the results by simulation. The theoretical results are
described in Izmirlian, G (2020) Statistics and Probability letters,
"<doi:10.1016/j.spl.2020.108713>", and an applied paper describing the
methodology with a simulation study is in preparation.
See citation("pwrFDR").

Grant Izmirlian

pwrFDR

FDR Power

es.ROC function

<dl> <dt>FPR0</dt>
<dd>When the TPR is fixed, the FPR under the null. Otherwise the fixed FPR.</dd> <dt>FPR1</dt>
<dd>When the TPR is fixed, the FPR under the alternative. Otherwise left blank.</dd> <dt>TPR0</dt>
<dd>When the FPR is fixed, the TPR under the null. Otherwise the fixed TPR.</dd> <dt>TPR1</dt>
<dd>When the FPR is fixed, the TPR under the alternative. Otherwise left blank.</dd> <dt>b</dt>
<dd>Nominal slope of the ROC at FPR0. Taken to be 1 by default.</dd></dl>

Arguments

Grant Izmirlian &lt;izmirlian at nih dot gov&gt;

Author

Computes the equivalent Z-test effect size 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. — es.ROC

<dl>

 <dt>FPR0</dt>
<dd>When the TPR is fixed, the FPR under the null. Otherwise the fixed FPR.</dd>

 <dt>FPR1</dt>
<dd>When the TPR is fixed, the FPR under the alternative. Otherwise left blank.</dd>

 <dt>TPR0</dt>
<dd>When the FPR is fixed, the TPR under the null. Otherwise the fixed TPR.</dd>

 <dt>TPR1</dt>
<dd>When the FPR is fixed, the TPR under the alternative. Otherwise left blank.</dd>

 <dt>b</dt>
<dd>Nominal slope of the ROC at FPR0. Taken to be 1 by default.</dd>

</dl>

Computes the equivalent Z-test effect size in hypothesis tests
 involving the ROC. Included here with the intent that it can be
 used in conjunction with <code>pwrFDR</code> to allow power/sample
 size calculation for multiple tests of ROC curve based hypothesis.
 See details.

es.ROC: Computes the equivalent Z-test effect size 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

Usage

Value

Arguments

Author

References

See Also

Examples