satterApproxP

p-value of the sum of dependent chi-squared using
the Satterthwaite approximation for the degrees of freedom.

When using pooled p-values to adjust for multiple testing, there is an inherent balance that must be struck between rejection based on weak evidence spread among many tests and strong evidence in a few, explored in Salahub and Olford (2023) <arXiv:2310.16600>. This package provides functionality to compute marginal and central rejection levels and the centrality quotient for p-value pooling functions and provides implementations of the chi-squared quantile pooled p-value (described in Salahub and Oldford (2023)) and a proposal from Heard and Rubin-Delanchy (2018) <doi:10.1093/biomet/asx076> to control the quotient's value.

Chris Salahub

PoolBal

Balancing Central and Marginal Rejection of Pooled p-Values

satterApproxP function

<dl><dt>qs</dt>
<dd>M numeric values (observed chi-squared values)</dd>
<dt>covmat</dt>
<dd>M by M covariance matrix of qs</dd>
<dt>kappa</dt>
<dd>degrees of freedom of qs</dd></dl>

Arguments

Author

Satterthwaite p-values — satterApproxP

<dl>

<dt>qs</dt>
<dd>M numeric values (observed chi-squared values)</dd>


<dt>covmat</dt>
<dd>M by M covariance matrix of qs</dd>


<dt>kappa</dt>
<dd>degrees of freedom of qs</dd>

</dl>

satterApproxP: Satterthwaite p-values

Description

Usage

Value

Arguments

Author

Details