I am a 4th year graduate student in the Political Science department of the University of Illinois at Urbana-Champaign, also pursuing a Master's Degree in Statistics. My research interests focus on how democratic institutions influence behavior at the both the elite and mass levels. With a background working on election campaigns and in non-profits, my years of practical experience inform my theory and design. I am currently attempting to separate the effects of elections from the effects of democracy, which are typically intertwined in political research.
In addition to election work, I've also worked as a computer programmer. I continue to put my technical skills into practice. Among other projects, I develop statistical packages to serve my needs as a practicing political scientist. Additionally, I have a strong interest in Political Science methodology. I am especially concerned about the reproducibility of research and how the tools we use shape the questions we ask.
At the St. Louis Area Methods Meeting, another participant pointed out that my previous SLAMM posting promised a follow up that never came. Oops. In lieu of actually finishing that report, I offer notes from the 2012 event.
Kosuke Imai started the conference discussing the relationship between regression with fixed effects and a series of alternative techniques for estimating average causal effects. Imai did an excellent job of motivating the comparisons and showing how, with appropriate weighting, many approaches are special cases of fixed effect regression. I think this will be an important paper in obviating the “regression vs. matching” debate. As a contributor to Optmatch, a R package for matching, I am interested to see how to translate specific matching strategies into regression weights. Imai showed several simple matching techniques (such as matching within covariate strata), but it was not immediately clear how to generalize to arbitrary matching schemes.
After lunch, Jake Bowers and I presented work on testing complex and substantively interesting models on experimental data. Jake began by setting scene and considering the problem of evaluating models in the presence of interference. I picked up the story by showing off the software we used and demonstrating with a different example.
My presentation had a fair amount of code demonstration. The SLAMM audience is usually a more technical one, so we were willing to risk showing some R code in the hopes that it would provide a concrete basis for understanding. It is not a technique that I would recommend for most audiences, but my sense was that it worked for the sharp folks in attendence.
During my presentation, Jonathan Olmsted from the University of Rochester was kind enough to grab a few photos on my camera.
The final presentation was from Jacob Montgomery (Washington University) and Josh Culter (Duke University) on Computer Adapative Testing in political surveys. This was one of those “why didn’t I think of that?” papers that immediately appeals to you. The basic idea is that we can improve on knowledge batteries and other components of surveys by selecting subequent questions based on earlier answers. Using the same techniques from computered testing such as the GRE, we do not need to ask a long battery to get a good estimate of a respondents traits.
This was an interesting paper because it also stimulated me to think along alternative lines, but with a similar goal. Much of CAT research, and this paper in particular, is very concerned with building a model of latent trait, i.e. something we think we can measure only indirectly through other means. I certainly spend a lot of time thinking about model building (my presentation was largely devoted to that), I would focus more prediction. Given a large training set of respondents who have completed a very a large battery, can I predict overall scores using only a subset of the questions. In other words, if a person has seen questions A and B, which other single question should I pick if I best wanted to estimate his or her total score on all the questions? This is a very similar question to the one posed by Montgomery and Cutler, but just shifts the emphasis on prediction rather than model construction. Different strokes for different folks.
The organizers and sponsors of SLAMM should be congradulated for putting on another successful conference. This is my 4th (of 5 possible) SLAMMs. They have all been extremely interesting. You can see all the pictures on Flickr.