average.power.t.test: Compute average power of many t-tests

In FDRsamplesize2: Computing Power and Sample Size for the False Discovery Rate in Multiple Applications

Compute average power of many t-tests

Description

Compute average power of many t-tests; Uses classical power formula for t-test; Assumes equal variance and sample size

Usage

average.power.t.test(
  n,
  alpha,
  delta,
  sigma = 1,
  type = "two.sample",
  alternative = "two.sided"
)

Arguments

n	per-group sample size (scalar)
alpha	p-value threshold (scalar)
delta	difference of population means (vector)
sigma	standard deviation (vector or scalar, default=1)
type	type of t-test: "two.sample", "one.sample"
alternative	one- or two-sided test

Value

Average power estimate for multiple testing procedure

Examples

d = rep(c(2,0),c(100,900));
average.power.t.test(n = 20, alpha = 0.05,delta = d)

FDRsamplesize2 documentation built on May 29, 2024, 7:12 a.m.