I’ve been playing around with the R package texreg for creating combined regression tables for multiple models. It’s not the only package to do that – see here for a review – but it’s often handy to be able to generate both ascii art, latex, and html versions of the same table using almost identical syntax. Also, the ascii art creating screenreg function allows me to bypass the pdf construction cycle I previously described here. The coefficient plots from plotreg are pretty cool too.
This post is about making the variables listed in those combined regression tables more readable. That is particularly important when data comes from variable-mangling statistical software or from co-authors whose idea of a descriptive name could pass for an online banking password. Even R will cheerfully mash up your carefully chosen variable names through formulas, factors, and interactions. So for work people are going to see, variables should have sensible names.
First I’ll walk through the existing texreg machinery for renaming, omitting, and reordering variables, and then propose a hopefully more intuitive implementation. I’ll demonstrate all this using screenreg on a classic data set on job prestige.
There are now quite a few R packages to turn cross-tables and fitted models into nicely formatted latex. In a previous post I showed how to use one of them to display regression tables on the fly. In this post I summarise what types of R object each of the major packages can deal with.
Unsurprisingly, there’s quite some variation…
Since it seems to be the fashion, here’s a post about how I make my academic papers.
Actually, who am I trying to kid? This is also about how I make slides, letters, memos and “Back in 10 minutes” signs to pin on the door. Nevertheless it’s for making academic papers that I’m going to recommend this particular set of tools.
I use the word make deliberately because I’m thinking of ‘academic paper’ broadly, as the sum of its words, analyses, tables, figures, and data. In this sense, papers can contain their own replication materials and when they do it should be possible in a single movement to rerun a set of analyses and reconstruct the paper that reports them.
To get anywhere near that goal, I use a mix of latex, its newer bibliography system biblatex, and the R package knitr. Also, I use a Mac, though that won’t make very much difference to the exposition.
Here’s how this currently works…
fourfive R packages will turn your regression models into pretty latex tables: texreg, xtable, apsrtable, memisc, and stargazer. This is very nice if you happen to be a latex document or its final reader, but it’s not so great if you’re making those models to start with.
What if you wanted to see these as you were working on them? In particular what if you wanted to see all your models lined up as if they were already Table 4 of the Masterwork Yet To Be Named that is only now slowly taking shape in your mind?