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Political Analysis Advance Access originally published online on March 1, 2005
Political Analysis 2005 13(2):157-170; doi:10.1093/pan/mpi009
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Political Analysis Vol. 13 No. 2, © The Author 2005. Published by Oxford University Press on behalf of the Society for Political Methodology. All rights reserved. For Permissions, please email: journals.permissions@oupjournals.org

A Solution to Separation in Binary Response Models

Christopher Zorn

Law and Social Science Program, National Science Foundation, 4201 Wilson Boulevard, Suite 995, Arlington, VA 22230
e-mail: czorn{at}nsf.gov

A common problem in models for dichotomous dependent variables is "separation," which occurs when one or more of a model's covariates perfectly predict some binary outcome. Separation raises a particularly difficult set of issues, often forcing researchers to choose between omitting clearly important covariates and undertaking post–hoc data or estimation corrections. In this article I present a method for solving the separation problem, based on a penalized likelihood correction to the standard binomial GLM score function. I then apply this method to data from an important study on the postwar fate of leaders.


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