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Simulating Duration Data for the Cox Model

Published online by Cambridge University Press:  24 May 2018

Jeffrey J. Harden  and
Jonathan Kropko
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Abstract

The Cox proportional hazards model is a popular method for duration analysis that is frequently the subject of simulation studies. However, no standard method exists for simulating durations directly from its data generating process because it does not assume a distributional form for the baseline hazard function. Instead, simulation studies typically rely on parametric survival distributions, which contradicts the primary motivation for employing the Cox model. We propose a method that generates a baseline hazard function at random by fitting a cubic spline to randomly drawn points. Durations drawn from this function match the Cox model’s inherent flexibility and improve the simulation’s generalizability. The method can be extended to include time-varying covariates and non-proportional hazards.

Information

Type
Research Notes
Information
Political Science Research and Methods , Volume 7 , Issue 4 , October 2019 , pp. 921 - 928
Copyright
© The European Political Science Association 2018 

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Footnotes

*

Jeffrey J. Harden is an Assistant Professor in the Department of Political Science, University of Notre Dame, 2055 Jenkins Nanovic Halls, Notre Dame, IN 46556 (jeff.harden@nd.edu). Jonathan Kropko is an Assistant Professor of in the Department of Politics, University of Virginia, S383 Gibson Hall, 1540 Jefferson Park Avenue, Charlottesville, VA 22904 (jkropko@virginia.edu). The methods described here are available in the coxed R package. To view supplementary material for this article, please visit https://doi.org/10.1017/psrm.2018.19

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Supplementary material: Link

Harden and Kropko Dataset

Dataset

https://doi.org/10.7910/DVN/1YG7BI
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Harden and Kropko supplementary material

Harden and Kropko supplementary material

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