########################################################################## # Copyright, 2013, Arianna Morgan ## ########################################################################## ## The programmes in this repository are free software: you can ## ## redistribute them and/or modify them under the terms of the GNU ## ## General Public License as published by the Free Software Foundation, ## ## either version 3 of the License, or (at your option) any later ## ## version. ## ## ## ## These program are distributed in the hope that they will be useful, ## ## but WITHOUT ANY WARRANTY; without even the implied warranty of ## ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the ## ## GNU General Public License for more details. ## ########################################################################## This repository contains a series of R functions under development that are intended to simulate power analyses. I am developing these scripts in order to provide easier ways to do power simulations in R for tests that have analytic power solutions (e.g. t-tests, ANOVA, regression, etc.) as well as more complex instruments such as mixed-effects models. Goals of this project: *Develop simulation scripts for: -t-tests -ANOVA -Multiple Regression -Mixed-Efffect models -Other tests *Provide thoroughly commented R code so that it is easy to understand my reasons for writing the simulations as I did. I have noticed that much of the power simulation code out there is hard-to-follow with respect to what the code is doing and why it is being done that way. *Make power simulations in general easier to run and more accessible to users outside the R community. In order to increase interest in R and reduce our colleagues' dependence on non-Free software, code needs to be commented clearly and thoroughly for newcomers to better understand it. I have become frustrated with trying to use code to figure out what exactly I am trying to do in general with power analysis simulations. *Create functions that are tools for teaching both statistics and R program- ming. For many people R is a way to implement statistical instruments they already know about. For others, though, R can become an essential part of (on-going) statistical education. For those who tinker with code as a way to learn about stats, I hope these functions will be of use to you. *Make the best functions possible for power simulations through experimenta- tion and the incorporation of code suggestions and contributions from others. If you want to make suggestions or repurpose the code in this repo, please do! I would love to see any modifications that people make to these scripts.