Welcome to QAPS
The Program for Quantitative and Analytical Political Science (QAPS) was established in 2009 to support theoretical and quantitative research in political science and its dissemination. We support graduate students through QAPS fellowships, host post-doctoral research fellows, offer statistical and formal theory consulting, hold quantitative skills workshops, throw conferences, and organize the Quantitative Social Science Colloquium.
Future Events
News
Our long-serving director, Kristopher Ramsay, has taken on a new role as interim department chair. We would like to express our heartfelt gratitude to Kris for his many years of dedicated service at QAPS. We wish him all the best in his new position, where he will continue to make significant contributions to the department.
We are also thrilled to announce that Arthur Spirling, Germán Gieczewski, and Gleason Judd have joined Rocio Titiunik, who has served alongside Kris Ramsay for many years, in leading QAPS. We warmly welcome and look forward to working with the new leadership team as we continue our mission to provide statistical services, support for research,…
Previous Events
TBA
Randomization inference (RI) is typically interpreted as testing Fisher's "sharp" null hypothesis that all unit-level effects are exactly zero. This hypothesis is often criticized as restrictive and implausible, making its rejection scientifically uninteresting. We show, however, that many randomization tests are also valid for a "bounded" null…
The next QAPS workshop will be on Writing Mathematical Notation Using Overleaf/LaTeX,. This workshop is designed as a supplementary workshop for, but is not exclusive to, POL502 students. Any graduate student concerned with creating mathematical notation for papers and assignments are welcome to attend. The workshop will…
Election forensics is the use of statistical methods to determine whether the results of an election accurately reflect the intentions of the electors. The eforensics model is a finite mixture measurement model that uses Bayesian methods to produce valid (but imperfect) aggregation unit estimates of the incidence and magnitude of realized…