SimTtestPower: Two-Sample Power Calculation Based on Simulation
In FeronG/ClassExample:

Description Usage Arguments Details Value Examples

View source: R/Code9.R

Power is the probability we reject the null hypothesis given it is false. Building on this definition, create a function that uses simulations to estimate power for a two-sample T-test.

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SimTtestPower(Var1mean = NULL, Var2mean = NULL, Var1sd = NULL,
  Var2sd = NULL, Var1samplesize = NULL, Var2samplesize = NULL,
  nsim = 100, alphalevel = 0.05)

`Var1mean`	Variable 1 mean
`Var2mean`	Variable 2 mean
`Var1sd`	Variable 1 standard deviation
`Var2sd`	Variable 2 standard deviation
`Var1samplesize`	Variable 1 sample size
`Var2samplesize`	Variable 2 sample size
`nsim`	Number of simulations
`alphalevel`	alpha-level (default=0.05)

First, you will need to simulate two normally distributed variables, each with a distinct sample size, mean, and standard deviation, and perform a T-test. For that single simulation, evaluate if we would reject the null hypothesis given a specific alpha-level. Now repeat this simulation many times. Power can then be estimated as the proportion of simulations for which we rejected the null hypothesis.

Empirical power calculation