The “Stata Logs” show how to reproduce the result of (practically) all the analysis in my lecture notes on Generalized Linear Models. The material is organized by Chapters and Sections using exactly the same numbering system as the notes, so section 2.8 of the logs deals with the analysis of covariance models described in section 2.8 of the notes.
The logs combine a narrative with actual Stata commands and output. The text boxes set in a typewritter font contain commands or instructions to Stata, followed by the resulting output. You can tell the commands apart because they appear on lines beginning with a dot, or on continuation lines beginning with a greater than sign. The overall format is similar to that used in the Stata manuals themselves.
The best way to use these transcripts is sitting by a computer, trying the different commands as you read along, probably with a printed copy of the notes by the side. I also recommend that you try to answer the few questions and exercises posed along the way. If you follow this procedure you will notice that sometimes I use the continuation comment /// to indicate that a command continues on another line. If you are using Stata interactively, just keep typing on the command window and the text will wrap.
While interactive use is probably good for learning, for more serious work I recommend that you prepare your commands in a “do file” and then ask Stata to run it. If nothing else, this will help document your work and ensure that you can reproduce your results.
Even better, use the markstat command
to combine a narrative written in Markdown with Stata commands and output.
These logs were all produced using markstat, and you will find the source
code on GitHub, just follow the link near the top-right of very log.
The “Stata Logs” were first published in January 1993 and targeted Stata version 3. Revisions were completed to target newer releases roughly every couple of years. The current edition was run using Stata 17 and was last updated in the Fall of 2022.
P.S. The Anscombe datasets are here