Power analysis tool for experimental and quasi-experimental designs
Project description
pypowerup
pypowerup is the Python implementation for the research article "PowerUp!: A Tool for Calculating Minimum Detectable
Effect Sizes and Minimum Required Sample Sizes for Experimental and Quasi-experimental Design Studies (Dong & Maynard, 2013)". It is a
power analysis tool for experimental and quasi-experimental designs.
References
Dong, N. & Maynard, R. A. (2013). PowerUp!: A tool for calculating minimum detectable effect sizes and minimum required sample sizes for experimental and quasi- experimental design studies, Journal of Research on Educational Effectiveness, 6(1), 24-67. doi: 10.1080/19345747.2012.673143. https://www.causalevaluation.org/uploads/7/3/3/6/73366257/powerup.xlsm
Bulus, M., Dong, N., Kelcey, B., & Spybrook, J. (2019). PowerUpR: Power Analysis Tools for Multilevel Randomized Experiments. R package version 1.0.4. https://CRAN.R-project.org/package=PowerUpR
History
0.1.0 (2020-9-19)
- First release on PyPI.
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