hrQ: Empirical UMP beta centrality quotient

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

Empirical UMP beta centrality quotient

Description

Estimates the centrality quotient for the UMP pooled p-value of a restricted beta family.

Usage

hrQ(w, alpha = 0.05, M = 2, nsim = 1e+05)

Arguments

w	numeric between 0 and 1
alpha	numeric between 0 and 1
M	integer sample size greater than 0
nsim	integer, the number of simulated null cases generated

Details

The centrality quotient communicates the tendency for a test to favour evidence shared among all tests over strong evidence in a single test.

To test the null hypotheses that all p-values are uniform against a restricted beta family 0 < a <= 1 <= b, the most powerful pooled p-value linearly combines upper and lower tail probabilities of the chi-squared distribution with two degrees of freedom with weights w and (1 - w) where w = (1 - a)/(b - a).

This function uses the individual estimation functions for central and marginal rejection levels to compute the centrality quotient for the UMP pooled p-value.

Value

An empirical estimate of the centrality quotient.

Author(s)

Chris Salahub

Examples

hrQ(0.8, alpha = 0.05, M = 10)

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