power: Power of Fisher's Exact Test for Comparing Proportions

In statmod: Statistical Modeling

Power of Fisher's Exact Test for Comparing Proportions

Description

Calculate by simulation the power of Fisher's exact test for comparing two proportions given two margin counts.

Usage

power.fisher.test(p1, p2, n1, n2, alpha=0.05, nsim=100, alternative="two.sided")

Arguments

p1	first proportion to be compared.
p2	second proportion to be compared.
n1	first sample size.
n2	second sample size.
alpha	significance level.
nsim	number of data sets to simulate.
alternative	indicates the alternative hypothesis and must be one of "two.sided", "greater" or "less".

Details

Estimates the power of Fisher's exact test for testing the null hypothesis that p1 equals p2 against the alternative that they are not equal.

The power is estimated by simulation. The function generates nsim pairs of binomial deviates and calls fisher.test to obtain nsim p-values. The required power is tnen the proportion of the simulated p-values that are less than alpha.

Value

Estimated power of the test.

Author(s)

Gordon Smyth

See Also

fisher.test, power.t.test

Examples

power.fisher.test(0.5,0.9,20,20) # 70% chance of detecting difference

statmod documentation built on Jan. 6, 2023, 5:14 p.m.