Political Analysis Advance Access published online on May 18, 2005
Political Analysis, doi:10.1093/pan/mpi014
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1 New York University, Department of Politics, 726 Broadway, 7th Floor, New York, NY 10003
* To whom correspondence should be addressed.
Multiplicative interaction models are common in the quantitative political science literature. This is so for good reason. Institutional arguments frequently imply that the relationship between political inputs and outcomes varies depending on the institutional context. Models of strategic interaction typically produce conditional hypotheses as well. Although conditional hypotheses are ubiquitous in political science and multiplicative interaction models have been found to capture their intuition quite well, a survey of the top three political science journals from 1998 to 2002 suggests that the execution of these models is often flawed and inferential errors are common. We believe that considerable progress in our understanding of the political world can occur if scholars follow the simple checklist of dos and don'ts for using multiplicative interaction models presented in this article. Only 10% of the articles in our survey followed the checklist.
Article
Understanding Interaction Models: Improving Empirical Analyses
2 University of Michigan, Center for Political Studies, ISR 4202 Box 1248, 426 Thompson Street, Ann Arbor, MI 48106-1248
3 Florida State University, Department of Political Science, 531 Bellamy Building, Tallahassee, FL 32306-2230
Matt Golder, E-mail: matt.golder{at}nyu.edu
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