Garret Christensen —BITSS Project Scientist
For whatever reason, economists use a lot of Stata. It does what we want to do (data cleaning, regression analysis, data visualization) well, and the $1,000 fees we pay every other version or so doesn’t seem to have stopped its widespread adoption. But is that changing, and are people switching to R and/or Python? I have no good data on the question, but it does seem obvious that if you’re teaching students who won’t be going to grad school in economics, requiring them to use Stata instead of R is pointlessly harmful to their job prospects in the tech sector.
Second, the dynamic documents and reproducible workflow capabilities of R Markdown and knitr, and version control, which are all built right into R Studio, blow anything I’ve seen in Stata out of the water. (Link to what I’ve seen in Stata.)
Third, it’s nice to be able to have more than one dataset in memory at the same time. And lot of other things like that.
With that in mind, I’m looking around for resources designed to help Stata users learn R. If I get time I’d like to develop a Software Carpentry-style lesson for it. The resources I’ve found so far are:
- Bob Muenchen’s website and book: r4stats.com
- Mostly Harmless Econometrics in four languages: R, Stata, Julia, Python
- A one page guide to dplyr tools and their Stata analogs.
Does anyone else have other resources? Experience or suggestions on making (and/or teaching) the switch?