# superb 0.9.7.8 (December 10th, 2021)

* Corrected a few typos.
* The population size in superbShiny() was limited to 99,999. Corrected.

# superb 0.9.7.7 (November 19th, 2021)

* Added a vignette for superb with SPSS
* Corrected superbShiny to show the doi and remove graphic directives
* Updated the shinyapps.io version to match this one

# superb 0.9.7.6 (November 4th, 2021)

* corrected one bug regarding variables with similar names
* integrated tibble data format into superb
* some output were missing in VignetteC and a backtick missing in VignetteA


# superb 0.9.7.5 (June 23rd, 2021)

* official release on CRAN of ``superb`` with the graphical user interface
``superbShiny()``;
* small changes to vignette TheMakingOf;


# superb 0.9.7.4 (June 18th, 2021)

* beta release of ``superbShiny()``, a graphical user interface to facilitate the
use of superbPlot.

# superb 0.9.7.0 (May 28th, 2021)

* Added a vignette on how to implement Reference Intervals (RI) into ``superb``;
* Implemented ``makeTransparent()`` to ease the creation of plots with multiple error bars;
* Added a distinct vertical color, ``vcolor``, to the ``geom_superberrorbar()``;
* Added an argument "WSDesign" (default = "fullfactorial") when the within-subject
    factors are not full-factorial;
* Added a vignette on how to plot non-full factorial datasets.

# superb 0.9.6.0 (April 30th, 2021)

* Integrated an example of robust statistic in Vignette/Article 4: 
   the 20% trimmed mean and its confidence interval;
* Added ``showSignificance()`` to annotate group differences;
* Added a note when missing data are in the dataframe;
* Added automatic handling of initializers (see Vignette/Article 9 for an example);
* Added a vignette dedicated to how to illustrate Cohen's d;
* Added a ``geom_superberrorbar()`` with additional options for the tip markers;
* ... all this on its way to the next release version 0.9.7.5, codename: 
   "two-tail 95% confident". Stay tune as the best is still to come (and it is shiny!)


# superb 0.9.5.0 (April 13th, 2021)

* Second release on CRAN, codename "95% confident"
* Expanded documentation once more


# superb 0.9.4.7 (April 10th, 2021)

* Added two vignettes


# superb 0.9.4.6 (April 7th, 2021)

* Problem with CAPITAL grd corrected
* Rounded the numbers in the messages to 4 decimals (that should be more than enough!)
* All the message/warnings/stop generated by suberb are now prefixed with "superb::"
* Added function WelchDegreeOfFreedom()
* Added a message that indicate tryon adjustment value
* Added a vignette on Welch, Tryon & superb


# superb 0.9.4.5 (April 1st, 2021)

* Implemented the raincloud plots
* Converted messages from warning() to message()


# superb 0.9.4.4 (March 2021)

* Expanded function names lambda, epsilon
* Made built-in bootstrap estimators for SE and PI
* Renamed option "debug" into "feedback"
* Changed debug information for GRD
* Converted in GRD the level ranges, e.g., "diff(1,5)", into numeric levels


# superb 0.9.4.3 (March 2021)

* Added superbData as a shortcut to superbPlot(... showPlot = FALSE)
* Changed debug information for suberbPlot and superbData
* Created a logo and improved web pages
* Revised documentation


# superb 0.9.4.2 (March 2021)

* Initial release of the R version on CRAN
* Added optional argument facetParams to the plotting functions
* Made the plot function customizable
* Wrote vignettes


# superb 0.9.4.0 (September 2020)

* Beta release of superb on GitHub
* Renamed to superb (SUmmary Plot with ERror Bars)
* packaged together GRD and MeanPlot
* Added pre and post-processing operators
* Transcoded MeanPlot from Mathematica to R


# GRD for R (version 1.0; January 2019)

* Initial release of GRD 2.0 for the R platform


# MeanPlot 0.5.0 (March 2017)

* Last stable version maintained on Mathematical; Cousineau (2017) doi:10.5709/acp-0214-z
* Updated legend manipulation following the release of Mathematica 9.0


# GRD for SPSS (versions 1.0 and 2.0; July 2014 and October 2015)

* Release of GRD 1.0 and 2.0 for SPSS


# MeanPlot 0.4.x and prior (2009-2015)

* Development versions of MeanPlot on the Mathematica framework 
* Added "popSize" and "CRS" from Cousineau & Laurencelle (2016) doi:10.1037/met0000055
* Grouped the various adjustments into an "adjustments" list
* Added LM decorrelation method

