What does the R-package 'superb' do?

Summary Plots with Adjusted Error Bars

Denis Cousineau, Bradley Harding, Marc-Andre Goulet, Jesika Walker

CRAN/E | superb

Computes standard error and confidence interval of various descriptive statistics under various designs and sampling schemes. The main function, superbPlot(), return a plot. superbData() returns a dataframe with the statistic and its precision interval so that other plotting package can be used. See Cousineau and colleagues (2021) doi:10.1177/25152459211035109 or Cousineau (2017) doi:10.5709/acp-0214-z for a review as well as Cousineau (2005) doi:10.20982/tqmp.01.1.p042, Morey (2008) doi:10.20982/tqmp.04.2.p061, Baguley (2012) doi:10.3758/s13428-011-0123-7, Cousineau & Laurencelle (2016) doi:10.1037/met0000055, Cousineau & O'Brien (2014) doi:10.3758/s13428-013-0441-z, Calderini & Harding doi:10.20982/tqmp.15.1.p001 for specific references.

Denis Cousineau

denis.cousineau@uottawa.ca

Customizing 'superb' plots
The making-of the figures in the article
Three steps to make your plot
Why use difference-adjusted confidence intervals?
Why use correlation-adjusted confidence intervals?
Using a custom statistic with its error bar within “superb“
Using a custom plot layout within “superb“
Generating ready-to-analyze datasets with GRD
Unequal variances, Welch test, Tryon adjustment, and “superb“
(advanced) Alternate ways to decorrelate repeated measures from transformations
Plotting Cohen's d with “superb“
Plotting Reference Intervals with “superb“
(advanced) Non-factorial within-subject designs in “superb“
Plotting proportions with “superb“
“superb“ and SPSS
Adding labels to “superb“ plots
Plotting frequencies using “superb“

superb archive

R

≥ 3.5.0

ANOFA