chiQ

Computes the centrality quotient of the chi-square
pooled p-value.

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

chiQ function

<dl><dt>kappa</dt>
<dd>numeric between 0 and infinity</dd>
<dt>M</dt>
<dd>integer sample size greater than 0</dd>
<dt>alpha</dt>
<dd>numeric between 0 and 1</dd></dl>

Arguments

Author

Chi-squared centrality quotient — chiQ

<dl>

<dt>kappa</dt>
<dd>numeric between 0 and infinity</dd>


<dt>M</dt>
<dd>integer sample size greater than 0</dd>


<dt>alpha</dt>
<dd>numeric between 0 and 1</dd>

</dl>

chiQ: Chi-squared centrality quotient

Description

Usage

Value

Arguments

Author

Details

Examples