Source: Long/Freese, Regression Models for Categorical Dependent Variables Using Stata
I use emacs/$latex LaTeX$for all my textprocessing needs, and for the last four or five years, I have created all my slides with Till Tantaus excellent “beamer” class. At the moment, I’m teaching a 2nd year stats course (imagine doing this with PowerPoint – the horror! the horror!), so I sometimes use graphs from the assigned text like this one from Long&Freese that illustrates the latent variable/threshold interpretation of the binary logit model. The message should be fairly clear: $latex y^{*}$ depends on $latex x$ andfollows a standard logistic distribution around its conditional mean.
Click to download the animated PDF. Requires javascript, so view in Acrobat reader.
But the fact that the bell-curve lies flat in the $latex x-y^{*}$ plane confused my students no end. So I wasted half a day on creating a nice 3d-plot for them. After trying several options, I settled on pgfplots.sty, which builds on tikz/pgf, the comprehensive, portable graphics package designed by Tantau (here’s a gallery with most amazing examples of what you can do with this little gem). Plotting data and functions with pgfplots in 2d or 3d is a snap, so that was not too hard. Eventually.
Finally, in a desperate attempt to drive the message home, I enlisted the help of animate.sty, yet another amazing package that creates a javascript-based inline animation from my $latex LaTeX$ source (requires Acrobat reader). So the bell-curves pop out of the plane, in slow motion. Did it help the students to see the light? I have no idea. Here is the source.
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