Announcing another slopegraph plotting function – June 14, 2018

June 13, 2018

(This article was first published on Chuck Powell, and kindly contributed to R-bloggers)

A couple of weeks ago I wrote a blog post about
. There was some
polite interest and it was a good chance to practice my functional
programming skills
I decided to see if I could make a decent R function from what I had
learned. It’s in pretty good shape so I just pushed an update to
CRAN (it will take awhile to process). You can also get the latest version from GitHub.

The documentation for it is here. Longer
term I hope to move it here.



The package also includes other functions that I find useful for teaching
statistics as well as actually practicing the art. They typically are
not “new” methods but rather wrappers around either base R or other
packages and concepts I’m trying to master.

  • Plot2WayANOVA which as the name implies conducts a 2 way ANOVA and
    plots the results using ggplot2
  • PlotXTabs which as the name implies plots cross tabulated
    variables using ggplot2
  • neweta which is a helper function that appends the results of a
    Type II eta squared calculation onto a classic ANOVA table
  • Mode which finds the modal value in a vector of data
  • SeeDist which wraps around ggplot2 to provide visualizations of
    univariate data.
  • OurConf is a simulation function that helps you learn about
    confidence intervals


# Install from CRAN

# Or the development version from GitHub
# install.packages("devtools")


Many thanks to Dani Navarro and the book > (Learning Statistics with
whose etaSquared function was the genesis of neweta.

“He who gives up safety for speed deserves neither.”

A shoutout to some other packages I find essential.

  • stringr, for strings.
  • lubridate, for date/times.
  • forcats, for factors.
  • haven, for SPSS, SAS and Stata
  • readxl, for .xls and .xlsx
  • modelr, for modelling within a
  • broom, for turning models into
    tidy data
  • ggplot2, for data visualisation.
  • dplyr, for data manipulation.
  • tidyr, for data tidying.
  • readr, for data import.
  • purrr, for functional programming.
  • tibble, for tibbles, a modern
    re-imagining of data frames.

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Contributions in the form of feedback, comments, code, and bug reports
are most welcome. How to contribute:

  • Issues, bug reports, and wish lists: File a GitHub
  • Contact the maintainer ibecav at by email.

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