estimatePc {PoolBal}

Compute the central rejection level

Description

Estimates the central rejection level for an arbitrary pooled p-value function.

Usage

estimatePc(
  poolFun,
  alpha = 0.05,
  M = 2,
  interval = c(0, 1),
  poolArgs = list(),
  ...
)

Arguments

poolFun

function accepting a vector of p-values

alpha

numeric between 0 and 1

M

integer, how many p-values are there?

interval

two numerics giving the bounds of root-searching

poolArgs

(optional) additional named arguments for poolFun

...

additional arguments to uniroot

Details

The central rejection level is the maximum p-value shared among all tests which still results in rejection of the null using a pooled p-value.

This function is essentially a wrapper for uniroot, and accepts a pooling function which takes a numeric vector as its first argument and potentially other arguments given in poolArgs and returns a single value. Using this pooling function, a specified dimension M and a rejection level alpha, uniroot searches for the root to poolFun - alpha along the line where all p-values are equal.

Value

The uniroot output.

Author(s)

Chris Salahub

Examples

tippool <- function(p) 1 - (1 - min(p))^(length(p))
estimatePc(tippool, 0.05, M = 10, interval = c(0, 1))