Worse than the bugs was the lack of proper scriptability. Pointing and clicking  loses its appeal when you need to run the same model on 12 different datasets, or when you are looking at three variants of the same model and 10 recodes of the same variable. Throw in the desire semi-automatically re-compile the findings from these exercises into two nice tables for inclusion in again and again after finding yet another problem with a model, and you will agree that any  piece of software that is not scriptable is pretty useless for scientists.

MLwiN’s command language was unreliable and woefully underdocumented, and everything was a pain. So I embraced xtmixed when it came along with Stata 9/10, which solved all of these problems.

runmlwin presentation (pdf)

But xtmixed is slow with large datsets/complex models. It relies on quadrature, which is exact but computationally intensive. MLwiN works with approximations of the likelihood function (quick and dirty) or MCMC (strictly speaking a Bayesian approach, but people don’t ask to many questions because it tends to be faster than quadrature). Moreover, MLwiN can run a lot of fancy models that xtmixed cannot, because it is a highly specialised program that has been around for a very long time.

Enter the good people over at the Centre for Multilevel Modelling at Bristol, who have come up with runmlwin, an ado that essentially makes the functionality of MLwiN available as a Stata command, postestimation analysis and all. Can’t wait to see if this works with Linux, wine and my ancient binaries, too.

Source: Long/Freese, Regression Models for Categorical Dependent Variables Using Stata

I use emacs/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: depends on 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 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 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.

Worldwide mutual citations in Political Science

Last Saturday, we presented our ongoing work on collaboration and citation networks in Political Science at the
4th UK Network conference held at the University of Greenwich. For this conference, we created a presentation on Knowledge Networks in European Political Science that summarises most of our findings on political science in Britain and Germany and provides some additional international context. The picture on the right shows a subnetwork of about 320 scientists who mutually cite each others’ work. Watch out for the dense IR/methods cluster and the lack of (mutual) connections between the dispersed political sociology and formal methods camps.

Technorati-Tags: sna, pajek, networks, analysis, political science, citation, bibliometrics, pdf, presentation


#New implicit rules for conversion of eps->mp->mps
#Change path if you have installed pstoedit in some other place
%.mp : %.eps
c:\pstoedit/pstoedit.exe -f mpost $*.eps $*.mp

%.mps: %.mp
mpost $*.mp
mv $*.1 $*.mps
rm $*.mp

#Now specify a target

presentation.pdf: presentation.tex mytab1.tex myfig.mps

#Optional: if you want to create dataset x.eps, run x.do
#Stata must be in your path
%.eps : %.do
\tab wstata -e do $<

Now type make presentation.pdf, and make will call Stata, pstoedit, metapost and pdflatex as required. If you need more figures, just write the do-file and add a dependency.

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Technorati Tags: make, latex, Makefile, Stata, political science, political, science, meta post, pstoedit, postscript, eps, pdf, pdflatex, beamer