Announcing another slopegraph plotting function -- June 14, 2018
Tagged as: [A couple of weeks ago I wrote a blog post about slopegraphs. There was some polite interest and it was a good chance to practice my functional programming skills so 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.
Overview
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.
Plot2WayANOVAwhich as the name implies conducts a 2 way ANOVA and plots the results usingggplot2PlotXTabswhich as the name implies plots cross tabulated variables usingggplot2newetawhich is a helper function that appends the results of a Type II eta squared calculation onto a classic ANOVA tableModewhich finds the modal value in a vector of dataSeeDistwhich wraps around ggplot2 to provide visualizations of univariate data.OurConfis a simulation function that helps you learn about confidence intervals
Installation
# Install from CRAN
install.packages("CGPfunctions")
# Or the development version from GitHub
# install.packages("devtools")
devtools::install_github("ibecav/CGPfunctions")
Credits
Many thanks to Dani Navarro and the book > (Learning Statistics with
R)
whose etaSquared function was the genesis of neweta.
“He who gives up safety for speed deserves neither.” (via)
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 files.
- readxl, for
.xlsand.xlsxfiles. - modelr, for modelling within a pipeline
- 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.
Leaving Feedback
If you like CGPfunctions, please consider leaving feedback here.
Contributing
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 issue.
- Contact the maintainer ibecav at gmail.com by email.