R for Stata Users: A Short Course

Introduction: R basics

Data basics

• Importing and exporting (Stata) data
• Basic R data structures and Stata equivalents
• How R and Stata manage data sets
• Viewing vs. modifying data in R and Stata
• Missing data

Recoding data

• Logical operators in R and Stata
• Common data recoding tasks

Essential R skills

• Understanding R’s functions and help files
• Writing understandable R code

Exploring data

• Descriptive statistics
• Exploratory data plots

Classic tests

• T-test
• Chi-squared test
• Storing and accessing test results in R and Stata

Linear models

• Fitting linear models
• Specifying common Stata options in R
• Post-estimation (time permitting)
  • Detecting and correcting problems
  • Model predictions

“I liked that the course referred back to my familiarity with Stata, but not overly so, and really focused on getting into the new software and doing some actual coding. It was exactly the gentle, stress-free start I needed to feel more confident, and less anxious, about learning and building my skills in R.”
  Angela Kemple, Washington State Department of Health

“The course starts you off slow and simple. This was the first time I could follow along with anything R after I was taught only Stata in my graduate program and told to go learn R on my own if I wanted to. I thought I might be somehow not tech-savvy enough for R when I tried to pick it up on my own. I no longer feel as though I am not cut out for R! I am actually ready to learn on my own now.”
  John Pippen, University of North Texas

“It was shorter than most SH courses and focused on applied issues with little theoretical background. It was well-organized. The instructor was pleasant, engaged, and effective – he did a great job. This would be a difficult course to teach, considering people’s questions about individual circumstances, technical challenges, etc., but Andrew did well juggling these issues. The course resources are really excellent. I took this course so as to leverage my existing knowledge of Stata and not have to learn R from scratch.”
  Jeff Hebert, University of New Brunswick

“In general, the pace and the pedagogical approach were very well chosen. More specifically, the instructor was very good at answering questions from the audience and using the chat function in an efficient manner to make it useful for everyone and not waste time. Not least, it was fun with Andrew!”
  Gunther Bensch, RWI – Leibniz-Institute for Economic Research

“I liked the instructor’s easy-going demeanor and his willingness to address students’ problems. I also liked his attitude that you need to familiarize yourself with R by coding in R.”
  John Fieno, Department of Health & Senior Services, State of Missouri

“I like the step-by-step approach, which made it clear what R programs to use that were comparable to common Stata commands when accessing, cleaning, and analyzing data.”
  Philip Ituarte, City of Hope National Medical Center

“This course was the right level for me – I have some modest experience in R but much more in Stata – so this helped me become more familiar with R. Two days was perfect for my time availability as well. The contextualization relative to Stata was very helpful.”
  Darren Courtney, Centre for Addiction and Mental Health