Would you be surprised to find out that the figures above were made in Stata? I discover the work of Daniel Bischof about a year ago and it has changed the way I think about Stata figures. I have been a long time user of ggplot2, the graphing R package by R Guru Hadley Wickham. Some of my publication figures using ggplot2 are dozens of lines long. I enjoy fiddling with every aspect of the aesthetic to make a perfectly clear visualization.
I prefer to create new log files every time I (fully) run a Stata script. When I’m writing a script or testing code I might stop logging, but in general it’s wise to keep logs of important runs. I store my logs in their own directory so that they don’t clog up my code directory (see organization). I title them with the scripts name followed by the date and time.
Some statistical jobs are either too memory-greedy or computationally intensive to run on a local machine. At the Johns Hopkins Medical Institutes (JHMI), researchers have access to a Linux cluster running a Oracle Grid Enginge (previously called the Sun Grid Engine). Jobs on the Joint HPC Exchange (JHPCE) can be run interactively with the qrsh command or through a qsub bash submission. JHPCE also has Stata-MP installed so that’s another reason why I use it for larger jobs.