power.twosampt: Compute power of the two-samples t-test

In FDRsampsize: Compute Sample Size that Meets Requirements for Average Power and FDR

Description

Estimate power of the two-samples t-test;Uses classical power formula for two-sample t-test;Assumes equal variance and sample size

Usage

power.twosampt (n, alpha, delta, sigma = 1) 

Arguments

n	per-group sample size (scalar)
alpha	p-value threshold (scalar)
delta	difference between population means (vector)
sigma	standard deviation (vector or scalar)

Details

For many applications, the null.effect is zero difference of means.

Value

vector of power estimates for two-sided test

Examples

 power.twosampt        # show the power function
 res=fdr.sampsize(fdr=0.1,
                  ave.pow=0.8,
                  pow.func=power.twosampt,
                  eff.size=rep(c(2,0),c(100,900)),
                  null.effect=0,
                  sigma=1)
 res

Example output

function (n, alpha, delta, sigma = 1) 
{
    1 - pf(qf(1 - alpha, 1, 2 * (n - 1)), 1, 2 * (n - 1), ncp = n * 
        (delta/sigma)^2/2)
}
<environment: namespace:FDRsampsize>
          n       alpha     ave.pow     fdr.hat     act.fdr 
8.000000000 0.008087158 0.800038317 0.083392914 0.083389697 

FDRsampsize documentation built on May 2, 2019, 9:14 a.m.