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Marginal Effects for Competing Risks Models with Piecewise Constant Hazards

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  • Tomi Kyyrä

Abstract

In the competing risks context, the effect of a covariate on the hazard function for a particular cause may be very different from its effect on the likelihood of exiting due to that cause. The latter probability is a function of all cause‐specific hazards, and thereby potentially affected by indirect effects via hazards for competing causes. We consider the effects of covariates on the cumulative probability of exiting from a particular cause. These ‘marginal effects’ are decomposed into direct effects via the hazard of interest and indirect effects via the hazards for competing causes. For the piecewise constant hazard specification we derive simple closed‐form expressions for the marginal effects that can be computed from the standard hazard function estimates. An empirical application illustrates that the marginal effects provide a useful and coherent way of summarizing the results of competing risks analysis.

Suggested Citation

  • Tomi Kyyrä, 2009. "Marginal Effects for Competing Risks Models with Piecewise Constant Hazards," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(4), pages 539-565, August.
  • Handle: RePEc:bla:obuest:v:71:y:2009:i:4:p:539-565
    DOI: 10.1111/j.1468-0084.2009.00551.x
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    References listed on IDEAS

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    1. Thomas, Jonathan M, 1996. "On the Interpretation of Covariate Estimates in Independent Competing-Risks Models," Bulletin of Economic Research, Wiley Blackwell, vol. 48(1), pages 27-39, January.
    2. Carling, Kenneth & Edin, Per-Anders & Harkman, Anders & Holmlund, Bertil, 1996. "Unemployment duration, unemployment benefits, and labor market programs in Sweden," Journal of Public Economics, Elsevier, vol. 59(3), pages 313-334, March.
    3. M. J. Andrews & S. Bradley & D. Stott, 2002. "Matching the Demand for and Supply of Training in the School-to-Work Transition," Economic Journal, Royal Economic Society, vol. 112(478), pages 201-219, March.
    4. J. P. Fine, 1999. "Analysing competing risks data with transformation models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(4), pages 817-830.
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