Description Usage Arguments Details Value Examples
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.
1 2 3 |
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
1 2 | SimTtestPower(Var1mean=20,Var2mean=22,Var1sd=4,Var2sd=6,
Var1samplesize=40,Var2samplesize=40,nsim=10000,alphalevel=0.05)
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