n.fdr.signtest

Find the sample size needed to have a desired false discovery rate and average power for a large number of sign tests.

Defines a collection of functions to compute average power and sample size for studies that use the false discovery rate as the final measure of statistical significance. A three-rectangle approximation method of a p-value histogram is proposed to derive a formula to compute the statistical power for analyses that involve the FDR. The methodology paper of this package is under review.

Yonghui Ni

FDRsamplesize2

Computing Power and Sample Size for the False Discovery Rate in
Multiple Applications

Stanley Pounds

n.fdr.signtest function

<dl><dt>fdr</dt>
<dd>desired FDR (scalar numeric)</dd>
<dt>pwr</dt>
<dd>desired average power (scalar numeric)</dd>
<dt>p</dt>
<dd>Pr(X&gt;0), as in Noether (JASA 1987)</dd>
<dt>pi0.hat</dt>
<dd>method to estimate proportion <code>pi0</code> of tests with true null, including: "HH" (p-value histogram height), "HM" (p-value histogram mean), "BH" (Benjamini &amp; Hochberg 1995), "Jung" (Jung 2005)</dd></dl>

Arguments

Sample size calculation for sign tests — n.fdr.signtest

<dl>

<dt>fdr</dt>
<dd>desired FDR (scalar numeric)</dd>


<dt>pwr</dt>
<dd>desired average power (scalar numeric)</dd>


<dt>p</dt>
<dd>Pr(X&gt;0), as in Noether (JASA 1987)</dd>


<dt>pi0.hat</dt>
<dd>method to estimate proportion <code>pi0</code> of tests with true null, including: "HH" (p-value histogram height), "HM" (p-value histogram mean), "BH" (Benjamini &amp; Hochberg 1995), "Jung" (Jung 2005)</dd>

</dl>

n.fdr.signtest: Sample size calculation for sign tests

Description

Usage

Value

Arguments

References

Examples