average.power.tcorr

Compute average power of many t-tests for non-zero correlation

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

average.power.tcorr function

<dl><dt>n</dt>
<dd>sample size (scalar)</dd>
<dt>alpha</dt>
<dd>p-value threshold (scalar)</dd>
<dt>rho</dt>
<dd>population correlation coefficient (vector)</dd></dl>

Arguments

Compute average power of many t-tests for non-zero correlation — average.power.tcorr

<dl>

<dt>n</dt>
<dd>sample size (scalar)</dd>


<dt>alpha</dt>
<dd>p-value threshold (scalar)</dd>


<dt>rho</dt>
<dd>population correlation coefficient (vector)</dd>

</dl>

average.power.tcorr: Compute average power of many t-tests for non-zero correlation

Description

Usage

Value

Arguments

Details

See Also

Examples