| hrQ {PoolBal} | R Documentation |
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)