The goal of Superpower
is to easily simulate factorial designs and empirically calculate power using a simulation approach. This package and its functions are intended to be utilized for prospective (a priori) power analysis. In addition to this site we have written a short book documenting a wide range of applications of this package and how to perform power analysis outside this R package using custom code.
You can install the most recent version of Superpower
from GitHub with:
devtools::install_github("arcaldwell49/Superpower")
Or you can install the stable version of Superpower from CRAN with:
install.packages("Superpower")
If you use Superpower
, please consider citing the following:
Lakens, D., & Caldwell, A. R. (2021). Simulation-Based Power Analysis for Factorial Analysis of Variance Designs. Advances in Methods and Practices in Psychological Science, 4(1), 251524592095150. https://doi.org/10.1177/2515245920951503
A BibTeX entry for LaTeX users is
@Article{,
doi = {10.1177/2515245920951503},
url = {https://doi.org/10.1177/2515245920951503},
year = {2021},
volume = {4},
number = {1},
pages = {251524592095150},
author = {Daniel Lakens and Aaron Caldwell},
title = {Simulation-Based Power Analysis for Factorial Analysis of Variance Designs},
journal = {Advances in Methods and Practices in Psychological Science},
}
We started this project to create a simple way to do ANOVA power calculations that the average experimental scientist can use. However, there are many cases that an ANOVA may not be appropriate. Therefore, we suggest using other packages such as simr
which allows for linear and generalized mixed models. Custom code can also be written and for such specialized simulations we highly recommend the simstudy
R package. For sequential analyses and adaptive designs the rpact
package will also be very helpful.