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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:


Or you can install the stable version of Superpower from CRAN with:



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.

A BibTeX entry for LaTeX users is

    doi = {10.1177/2515245920951503},
    url = {},
    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},

Other Simulation & Power Analysis Packages

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.

  • simstudy: Simulation of Study Data
  • faux: Simulate data with a specified structure.
  • simr: Power Analysis of Generalised Linear Mixed Models by Simulation
  • rpact: Confirmatory Adaptive Clinical Trial Design, Simulation, and Analysis
  • pwr: Basic functions for power analysis