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
Currently, there are no future events. Please contact us if you would like us to provide a methodology workshop that will benefit your research agenda.
News
We are happy to announce exciting updates from QAPS! We recently welcomed Tolgahan Dilgin as the QAPS Statistical Services Manager. For those who remember Will Lowe, Tolgahan will be serving in a very similar role. Stay tuned for updates on our upcoming workshops, and for information on how to utilize our consultancy services.
Previous Events
Consumer choices are increasingly mediated by algorithms, which use data on those past choices to infer consumer preferences and then curate future choice sets. Behavioral economics suggests one reason these algorithms so often fail: choices can systematically deviate from preferences. For example, research shows that prejudice can arise not…
According to theories of motivated reasoning, attempts to persuade political opponents are often counterproductive because they end up strengthening opponents' initial views via directional motivations. Drawing on evidence from 23 randomized survey experiments, Persuasion in Parallel shows that the predicted "backlash" fails to materialize…
Neural networks underlie state-of-the-art algorithms in a large and growing range of applied domains. That they work so well challenges long-held principles in statistics and optimization that have often guided applied work. This talk identifies and discusses several such points of tension between theory and practice and provide some heuristic…
The credibility revolution has promoted the adoption of research designs that permit identification and estimation of causal effects. Understanding which mechanisms drive measured causal effects remains a challenge. A dominant current approach to the quantitative evaluation of mechanisms relies on the detection of heterogeneous treatment…