Announcing CGPfunctions 0.3 – April 20, 2018

As I continue to learn and grow in using R I have been trying to develop the habit of being more formal in documenting and maintaining the various functions and pieces of code I write. It’s not that I think they are major inventions but they are useful and I like having them stored in one place that I can keep track of. So I started building them as a package and even publishing them to CRAN. For any of you who might find them of interest as well.

Overview

A package that includes 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. Currently contains:

• 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

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 .xls and .xlsx files.
• 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.