# SimTtestPower: Two-Sample Power Calculation Based on Simulation In alvancheng/ExamplePackage: Functions from Homework 2

## Description

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.

## Usage

 ```1 2 3``` ```SimTtestPower(Var1mean = NULL, Var2mean = NULL, Var1sd = NULL, Var2sd = NULL, Var1samplesize = NULL, Var2samplesize = NULL, nsim = 100, alphalevel = 0.05) ```

## Arguments

 `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)

## Details

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.

## Value

Empirical power calculation

## Examples

 ```1 2``` ```SimTtestPower(Var1mean=20,Var2mean=22,Var1sd=4,Var2sd=6, Var1samplesize=40,Var2samplesize=40,nsim=10000,alphalevel=0.05) ```

alvancheng/ExamplePackage documentation built on March 18, 2018, 6:45 p.m.