I ordered Carlin and Louis 2009 “Bayesian Methods for Data Analysis” yesterday and have been left with some questions by the first chapter that I want to raise here, because it reinforces my belief that there’s an unfortunate lacuna in this and many similar books. Specifically, is there a specific Bayesian approach to political science beyond what we think of as the Bayesian approach to statistical inference? I believe that our discipline conducts empirical testing primarily for the basis of making a convincing attempt at falsifying ourselves. If a tool is confusing to the median political scientist, can it ever be convincing? And for Bayesian statistics in particular, is an effort to fit the best model really an effort to falsify the theory?
Ben is currently an assistant professor in the Department of Environmental Studies at Knox College. He received his PhD in Political Science from Binghamton University in 2014. Ben was previously a visiting assistant professor in the Department of Political Science at Hobart and William Smith Colleges, and previously held a research position in the Department of Political Science at Fordham University. His research and teaching interests are centered around parties and interest groups, particularly those from under-represented constituencies. A great deal of his work deals with the political organizations of the environmental movement. He studies both American and Comparative politics.