chiPool: Chi-squared p-value pooling

In PoolBal: Balancing Central and Marginal Rejection of Pooled p-Values

Chi-squared p-value pooling

Description

This implements the chi-squared pooled p-value which can be used to control the centrality quotient when pooling p-values.

Usage

chiPool(p, kappa)

Arguments

p	numeric vector of p-values between 0 and 1
kappa	numeric value between 0 and infinity

Details

The chi-squared pooled p-value is a quantile transformation pooled p-value based on the chi-squared distribution with degrees of freedom kappa. By setting kappa between 0 and infinity, smooth interpolation is achieved between Tippett's minimum pooled p-value and Stouffer's normal quantile pooled p-value respectively. Choosing a kappa value of 2, Fisher's pooling function is obtained. Tippett's pooled p-value is maximally non-central and Stouffer's is maximally central, while Fisher's presents a balance between marginal and central rejection.

Value

A pooled p-value between 0 and 1.

Author(s)

Chris Salahub

Examples

p <- c(0.1, 0.5, 0.9)
chiPool(p, exp(-4))
chiPool(p, 2)
chiPool(p, exp(4))

PoolBal documentation built on Nov. 22, 2023, 5:07 p.m.