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Proportionally Difficult: Testing for Nonproportional Hazards in Cox Models

Published online by Cambridge University Press:  04 January 2017

Luke Keele
Luke Keele*
Affiliation:
Department of Political Science, 2140 Derby Hall, 150 North Oval Mall, Ohio State University, Columbus, OH 43210
*
e-mail: keele.4@polisci.osu.edu (corresponding author)
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Abstract

The Cox proportional hazards model is widely used to model durations in the social sciences. Although this model allows analysts to forgo choices about the form of the hazard, it demands careful attention to the proportional hazards assumption. To this end, a standard diagnostic method has been developed to test this assumption. I argue that the standard test for nonproportional hazards has been misunderstood in current practice. This test detects a variety of specification errors, and these specification errors must be corrected before one can correctly diagnose nonproportionality. In particular, unmodeled nonlinearity can appear as a violation of the proportional hazard assumption for the Cox model. Using both simulation and empirical examples, I demonstrate how an analyst might be led astray by incorrectly applying the nonproportionality test.

Type
Research Article
Information
Political Analysis , Volume 18 , Issue 2 , Spring 2010 , pp. 189 - 205
Copyright
Copyright © The Author 2010. Published by Oxford University Press on behalf of the Society for Political Methodology 

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Footnotes

Author's note: For helpful comments, I thank Jan Box-Steffensmeier, Mark Kayser, Irfan Nooruddin, and the anonymous reviewers. I also thank Hein Goemans for sharing his data.

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