[R] [R-pkgs] superb (version 0.9.5.0) released to CRAN

Denis Cousineau Den|@@Cou@|ne@u @end|ng |rom uott@w@@c@
Sat Apr 24 16:05:40 CEST 2021


Dear all, 

we are happy to announce that the package ``superb`` is now available on CRAN. 
https://CRAN.R-project.org/package=superb  

``superb`` (Summary statistics Plots with adjusted Error Bars) is a package that produces
plots of summary statistics with adjusted error bars. These bars are adjusted to
allow pairwise comparisons in both between and within-subject design (Baguley, 2012; https://doi.org/10.3758%2Fs13428-011-0123-7). 

The latest version 0.9.5.0 (Codename "95% confident") is a spin-off of the package 
``MeanPlot`` for Mathematica 10.0 and above (Cousineau, 2017; https://doi.org/10.5709/acp-0214-z).

With simple adjustments, you get raw confidence intervals or standard errors, but also
intervals adjusted for within-subject-designs and more.

The plots created are ggplot objects that can be fully customized for your purpose. The package generates advanced plots such as raincloud plots and violin plots, for example:
 

Examples for the usage of the main function ``superbPlot()``, the documentation of all functions, as well as vignettes can be found at 
https://dcousin3.github.io/superb/

If you notice a bug or have suggestions for improvements, please submit an issue with a minimal reproducible example at 
https://github.com/dcousin3/superb/issues/

A complete text describing the ``superb`` framework and philosophy is currently under 
considerations as Advances in Methods and Practices in Psychological Sciences.

Best, 
Denis Cousineau


Recipient of the 2021 mid-career award from the Canadian Society for Brain, Behavior and Cognitive Sciences
2020 APA Distinguished Scientific Awards for an Early Career Contribution to Psychology to M.-A. Goulet 
2016 R. Duncan Luce Outstanding Paper award for Learning curves as strong evidence for testing models: The case of EBRW

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