A Parametric Competing Risks Regression Model with Unknown Dependent Censoring

Simon M. S. Lo, Ralf A. Wilke*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

A typical situation in survival analysis is that there is only interest in one risk and some prior information about its distribution is available. At the same time, other risks are not of interest and no information about risk dependence is available. A parametric regression model with unknown dependent censoring would be suitable here, but existing approaches require restrictions on all marginal survivals, the censoring distribution or the degree of dependence. This article introduces a model without these restrictions. An application to employment duration demonstrates that it avoids sizable bias of the estimated gender effect on employment duration.
Original languageEnglish
JournalJournal of the Royal Statistical Society, Series C (Applied Statistics)
Volume72
Issue number4
Pages (from-to)1079–1093
Number of pages15
ISSN0035-9254
DOIs
Publication statusPublished - Aug 2023

Bibliographical note

Published online: 15 June 2023.

Keywords

  • Archimedean copula
  • Depending censoring
  • GMM estimation

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