.mdmr.permstats

Function to compute test statistics for a permuted design matrix

Allows users to conduct multivariate distance matrix regression using analytic p-values and compute measures of effect size. For details on the method, see McArtor, Lubke, & Bergeman (2017) <doi:10.1007/s11336-016-9527-8>.

Daniel McArtor

MDMR

Multivariate Distance Matrix Regression

Dan McArtor

.mdmr.permstats function

<dl><dt>X</dt>
<dd>A \(n x p\) matrix or data frame of predictors.</dd>
<dt>n</dt>
<dd>sample size</dd>
<dt>vg</dt>
<dd>Computational details (internal function)</dd>
<dt>trG</dt>
<dd>trace of G</dd>
<dt>px</dt>
<dd>Computational details (internal function)</dd>
<dt>test.inds</dt>
<dd>Computational details (internal function)</dd></dl>

Arguments

Function to compute test statistics for a permuted design matrix — .mdmr.permstats

<dl>

<dt>X</dt>
<dd>A \(n x p\) matrix or data frame of predictors.</dd>


<dt>n</dt>
<dd>sample size</dd>


<dt>vg</dt>
<dd>Computational details (internal function)</dd>


<dt>trG</dt>
<dd>trace of G</dd>


<dt>px</dt>
<dd>Computational details (internal function)</dd>


<dt>test.inds</dt>
<dd>Computational details (internal function)</dd>

</dl>

.mdmr.permstats: Function to compute test statistics for a permuted design matrix

Description

Usage

Arguments