ANOPA
Analyses of Proportions using Anscombe Transform
Analyses of Proportions can be performed on the Anscombe (arcsine-related) transformed data. The 'ANOPA' package can analyze proportions obtained from up to four factors. The factors can be within-subject or between-subject or a mix of within- and between-subject. The main, omnibus analysis can be followed by additive decompositions into interaction effects, main effects, simple effects, contrast effects, etc., mimicking precisely the logic of ANOVA. For that reason, we call this set of tools 'ANOPA' (Analysis of Proportion using Anscombe transform) to highlight its similarities with ANOVA. The 'ANOPA' framework also allows plots of proportions easy to obtain along with confidence intervals. Finally, effect sizes and planning statistical power are easily done under this framework. Only particularity, the 'ANOPA' computes F statistics which have an infinite degree of freedom on the denominator. See Laurencelle and Cousineau (2023) doi:10.3389/fpsyg.2022.1045436.
- Version0.1.3
- R version≥ 3.5.0
- LicenseGPL-3
- Needs compilation?No
- ANOPA citation info
- Last release03/22/2024
Documentation
- VignetteWhat is an Analysis of Proportions using the Anscombe Transform?
- VignetteData formats for proportions
- VignetteConfidence intervals with proportions
- VignetteAnalyzing proportions with the Arrington et al. 2002 example
- VignetteIs the ArcSine transformation so asinine in the end?
- VignetteTesting type-I error rates
- MaterialREADME
- MaterialNEWS
Team
Denis Cousineau
Louis Laurencelle
Show author detailsRolesAuthor, Contributor
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- Imports6 packages
- Suggests3 packages