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Proportionally Difficult: Testing for Nonproportional Hazards in Cox Models

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  • Keele, Luke

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.

Suggested Citation

  • Keele, Luke, 2010. "Proportionally Difficult: Testing for Nonproportional Hazards in Cox Models," Political Analysis, Cambridge University Press, vol. 18(2), pages 189-205, April.
  • Handle: RePEc:cup:polals:v:18:y:2010:i:02:p:189-205_01
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    15. Baccini, Leonardo, 2014. "Cheap talk: transaction costs, quality of institutions, and trade agreements," LSE Research Online Documents on Economics 44923, London School of Economics and Political Science, LSE Library.
    16. Allan Dafoe, 2018. "Nonparametric Identification of Causal Effects under Temporal Dependence," Sociological Methods & Research, , vol. 47(2), pages 136-168, March.
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