#  Tingley on "A Statistical Method for Empirical Testing of Competing Theories"  

 





February 09, 2011

 

 

Just a note about the [Applied Statistics Workshop](http://www.iq.harvard.edu/events/node/1208) today,February 9th, where we are excited to have [Dustin Tingley](http://scholar.harvard.edu/dtingley/home) from theDepartment of Government here at Harvard presenting joint work with [Kosuke Imai](http://imai.princeton.edu/) entitled [“A Statistical Method for Empirical Testing of Competing Theories”](http://imai.princeton.edu/research/mixture.html). As usual, the workshop will beginwith a light lunch at 12 noon, followed by the presentation at 12:15.

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.

Posted by [Matt Blackwell](http://www.iq.harvard.edu/blog/sss/archives/author/matt-blackwell/) at February 9, 2011 7:53 AM



 

 

 



 

 

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