The identifiability of the competing risks model

James J. Heckman; Bo E. Honoré

doi:10.1093/biomet/76.2.325

The identifiability of the competing risks model

James J. Heckman, Bo E. Honoré

Research output: Contribution to journal › Article › peer-review

183 Scopus citations

Abstract

This paper considers the consequences for identifiability of introducing regressors into the competing risks model of multistate duration analysis. We establish conditions under which access to regressors overturns the nonidentification theorem of Cox and Tsiatis for both proportional and accelerated failure time models.

Original language	English (US)
Pages (from-to)	325-330
Number of pages	6
Journal	Biometrika
Volume	76
Issue number	2
DOIs	https://doi.org/10.1093/biomet/76.2.325
State	Published - Jun 1 1989
Externally published	Yes

All Science Journal Classification (ASJC) codes

Statistics and Probability
Mathematics(all)
Agricultural and Biological Sciences (miscellaneous)
Agricultural and Biological Sciences(all)
Statistics, Probability and Uncertainty
Applied Mathematics

Keywords

Competing risks model
Identifiability
Regressor

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10.1093/biomet/76.2.325

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abstract = "This paper considers the consequences for identifiability of introducing regressors into the competing risks model of multistate duration analysis. We establish conditions under which access to regressors overturns the nonidentification theorem of Cox and Tsiatis for both proportional and accelerated failure time models.",

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KW - Regressor

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The identifiability of the competing risks model

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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