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alphaN: Set Alpha Based on Sample Size Using Bayes Factors
Sets the alpha level for coefficients in a regression model as a decreasing function of the sample size through the use of Jeffreys' Approximate Bayes factor. You tell alphaN() your sample size, and it tells you to which value you must lower alpha to avoid Lindley's Paradox. For details, see Wulff and Taylor (2024) <doi:10.1177/14761270231214429>. Alpha can also be calibrated to the effect-size and moment Bayes factors of Klauer, Meyer-Grant, and Kellen (2024) <doi:10.3758/s13423-024-02612-2>, which center the alternative hypothesis on an effect size of your choosing.
Getting started
Browse package contents
Package details |
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| Author | Jesper Wulff [aut, cre] (ORCID: <https://orcid.org/0000-0002-7976-0939>), Luke Taylor [aut] |
| Maintainer | Jesper Wulff <jwulff@econ.au.dk> |
| License | MIT + file LICENSE |
| Version | 0.2.0 |
| URL | https://github.com/jespernwulff/alphaN https://jespernwulff.github.io/alphaN/ |
| Package repository | View on CRAN |
| Installation |
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