Using the R Commander, a Book Review & Webinar Replay
The following book review was originally reported in the Fall 2016 newsletter. But given our March 2018 Webinar "Using the R Commander in Basic Statistics Courses" by John Fox, it seemed like a good time to share it again.
If you were unable to attend the Webinar in person, TSHS members can access the recording for free – a benefit of membership! Simply login at amstat.org and visit the TSHS eGroup in the ASA Community. The link is on the right hand side, with the presentation audio starting roughly at the 5 minute mark.
Title: Using the R Commander: A Point-and-Click Interface for R
Author: John Fox
Publisher: CRC Press
ISBN-13: 978-1498741903
Formats available: Paperback & eBook
Review by: Laila M Poisson, Book Review Editor (2016)
When interacting with data-savvy clinicians, researchers, and students, I often run into a big road block. They have data but don’t have access to good tools by which to analyze those data. While R is free, most folks were trained on point-and-click GUI-based software, or, have self-trained using macros on spreadsheets. Needless to say, command-line programming in R is perceived to be overwhelming. Enter the R Commander, a GUI that is built on top of R. While at JSM2016, I was delighted to pick up this book by John Fox, creator of the R Commander. I’m even more delighted to say that I found it to be a good read.
The book is an informative manual for the R Commander. The essential reads are Chapters 2-4, with supplements from the book’s online resource. Chapter 2, which covers how to set up the the R Commander, should be read before starting since it gives a few customizations for the installation of R to ensure that the GUI works properly. For instance, in a Windows environment, R should be installed using the Single Document Interface (SDI) mode. This is not the default (I had to re-install). For Mac, Linux, and Unix users, there are specific instructions for you too.
Chapter 3 provides a “quick tour” of The R Commander. The supporting website has all of the datasets required to replicate the analysis examples in the text. (I tried, they work!) The examples cover important concepts for analysis, such as how to recode categorical variables and summarize in a table. There are screen shots throughout to orient the reader. They end with a discussion about creating dynamic reports in HTML (default), Pandoc, or LaTeX. While dynamic reports may be foreign to some potential users, I appreciate this push toward reproducible research. Chapter 4 goes into more depth about data import, export, and management, which supports clean data for sensible analysis results.
The remaining chapters, cover specific analysis topics (ch. 5-8) and the use of plug-ins that extend the functionality of the GUI (ch 9). Basic analysis topics and graphics are presented as well-documented examples, with screen shots and option lists. In this way, once the reader is familiar with the GUI (ch 2-4), analysis topics can be picked up as needed. For instructors, be aware, the author specifically states that the objective of the text is to demonstrate how to use The R Commander rather than to provide instruction in basic statistical techniques. While the text covers the topics one might find in an introductory statistics course, this book is not sufficient as the primary text book.
In short, I’m excited to share this book with a few data-savvy colleagues who have expressed an interest in, but a hesitancy toward, using R to expand their analysis capacity. And since the R Commander allows you to save your code, for reproducibility and to share with other R users (like their statistician colleague), it’s also a gentle entry into command-line programming.