GenPMat: Generate p-value matrix for simulation

In jingshuw/adaFilter: Adaptive Filtering Multiple Testing Procedures for finding multiple replicating signals

Description

Generate p-value matrix for simulation

Usage

GenPMat(M = 1000, n = 2, r = 2, all.zero.frac = 0.5,
  alternative.frac = 0.1, mu = c(3, 4, 6), rho = 0,
  block.size = 10, one.sided = F)

Arguments

M	number of partial conjunction hypotheses
n	number of studies
r	the required minimum number of nonnull studies for a nonnull partial conjunction hypothesis
all.zero.frac	the fraction of complete nulls
alternative.frac	the total fraction nonnull partial conjunction hypotheses
mu	a vector of possible values of effect size of nonnull individual hypotheses
rho	correlation within block of screening tests
block.size	the block size of the block dependency structure
one.sided	either construct one-sided p-value or not

Value

a list of objects

truth.pc

a length M vector of 1 and 0s indicating whether the corresponding hypothesis is a true nonnull partial conjunction hypothesis or not

pvalue.mat

the individual p-value matrix of size M * n

zmat

The corresponding z-value matrix of size M * n

References

J. Wang, L. Gui, W. J. Su, C. Sabatti and A. B. Owen (2020). Detecting Multiple Replicating Signals using Adaptive Filtering Procedures

jingshuw/adaFilter documentation built on July 28, 2021, noon