@article {26690, title = {The Doctrinal Paradox and International Law}, journal = {University of Pennsylvania Journal of International Law}, volume = {34}, number = {1}, year = {2012}, pages = {67-148}, author = {Adam Chilton and Tingley, Dustin} } @article {20277, title = {Dead Certain: Confidence and Conservatism Predict Aggression in Simulated International Crisis Decision-Making}, journal = {Human Nature}, volume = {23}, number = {1}, year = {2012}, pages = {98-126}, author = {Dominic Johnson and Rose McDermott and Jon Cowden and Tingley, Dustin} } @article {3590, title = {A Statistical Method for Empirical Testing of Competing Theories}, journal = {American Journal of Political Science}, volume = {56}, number = {1}, year = {2012}, pages = {218-236}, abstract = { Empirical testing of competing theories lies at the heart of social science research. We demonstrate that a very general and well-known class of statistical models, called finite mixture models, provides an effective way of rival theory testing. In the proposed framework, each observation is assumed to be generated from a statistical model implied by one of the theories under consideration. Researchers can then estimate the probability that a specific observation is consistent with either of the competing theories. By directly modeling this probability with the characteristics of observations, one can also determine the conditions under which a particular theory applies. We discuss a principled way to identify a list of observations that are statistically significantly consistent with each theory. Finally, we propose several measures of the overall performance of a particular theory. We illustrate the advantages of our method by applying it to an influential study on trade policy preferences. }, url = {http://imai.princeton.edu/research/mixture.html}, author = {Kosuke Imai and Tingley, Dustin} }