Competing Risks Regression with Dependent Multiple Spells: Monte Carlo Evidence and an Application to Maternity Leave

Cäcilia Lipowski, Simon M. S. Lo, Shuolin Shi, Ralf A. Wilke*

*Corresponding author for this work

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Copulas are a convenient tool for modelling dependencies in competing risks models with multiple spells. This paper introduces several practical extensions to the nested copula model and focuses on the choice of the hazard model and copula. A simulation study looks at the relevance of the assumed parametric or semiparametric model for hazard functions, copula and whether a full or partial maximum likelihood approach is chosen. The results show that the researcher must be careful which hazard is being specified as similar functional form assumptions for the subdistribution and cause-specific hazard will lead to differences in estimated cumulative incidences. Model selection tests for the choice of the hazard model and copula are found to provide some guidance for setting up the model. The nice practical properties and flexibility of the copula model are demonstrated with an application to a large set of maternity leave periods of mothers for up to three maternity leave periods.
Original languageEnglish
JournalJapanese Journal of Statistics and Data Science
Issue number2
Pages (from-to)953-981
Number of pages29
Publication statusPublished - Dec 2021

Bibliographical note

Published online: 3. March 2021


  • Copula
  • Competing risks
  • Repeated occurrences
  • Maternity leave

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