Justify Your Alpha

Justify Your Alpha

Input parameters

Minimize or Balance Error Rates?:

Relative cost Type 1 and Type 2 errors:

Prior Probability of H1 compared to H0:

Power function:

Input parameters

Alpha level:

Sample Size:

Standardize N:

Justify Your Alpha: A Practical Guide

For an explanation why researchers should justify their alpha levels, see:

Lakens, D., Adolfi, F. G., Albers, C. J., Anvari, F., Apps, M. A. J., Argamon, S. E., … Zwaan, R. A. (2018). Justify your alpha. Nature Human Behaviour, 2, 168–171. https://doi.org/10.1038/s41562-018-0311-x

You can download the pre-print of this article at PsyArXiV

For a short introduction in why to lower your alpha level as a function of the sample size, see my blog post . For a short introduction on why and how to balance or minimize error rates, see my other blog post .

Get the code at GitHub

The best way to cite this app and the explanations of how to justify alpha levels in practice is through the preprint:

Lakens, D. (2019). Justify Your Alpha: A Practical Guide.