Cited by 1,868Statistical Methods and InferenceStatistical Distribution Estimation and ApplicationsProbability and Statistical Research

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Regression Analysis of Multivariate Incomplete Failure Time Data by Modeling Marginal Distributions

Wei, L. J., Lin, D. Y., Weissfeld, L.·1989·Journal of the American Statistical Association

DOI 10.1080/01621459.1989.10478873

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Abstract

Many survival studies record the times to two or more distinct failures on each subject. The failures may be events of different natures or may be repetitions of the same kind of event. In this article, we consider the regression analysis of such multivariate failure time observations. Each marginal distribution of the failure times is formulated by a Cox proportional hazards model. No specific structure of dependence among the distinct failure times on each subject is imposed. The regression parameters in the Cox models are estimated by maximizing the failure-specific partial likelihoods. The resulting estimators are shown to be asymptotically jointly normal with a covariance matrix that can be consistently estimated. Simultaneous inferential procedures are then proposed. Extensive Monte Carlo studies indicate that the normal approximation is adequate for practical use. The new methods allow time-dependent covariates, missing observations, and arbitrary patterns of censorship. They are illustrated with two real-life examples. For recurrent failure time data, various regression methods have been proposed in the literature. These methods, however, generally assume stringent structures of dependence among the recurrences of each subject. Moreover, as shown in the present article, they are rather sensitive to model misspecification.

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Self-citation

Authors: Wei, L. J., Lin, D. Y., & Weissfeld, L.
Affiliations: University of Wisconsin–Madison (US)
Harvard University (US)
University of Michigan (US)
ORCID: Wei, L. J.
Lin, D. Y.
Venue: Journal of the American Statistical Association
Publisher: Informa UK Limited
Published: 1989-12
Volume: 84
Issue: 408
Pages: 1065-1073
ISSN: 0162-1459 (ISSN-L)
1537-274X
DOI: 10.1080/01621459.1989.10478873
OpenAlex: W2092648747
Cited by: 1,868
References: 31
Citations by year: 2026: 29 · 2025: 45 · 2024: 33 · 2023: 33 · 2022: 76 · 2021: 67 · 2020: 74 · 2019: 66 · 2018: 68 · 2017: 52 · 2016: 83 · 2015: 79 · 2014: 104 · 2013: 91 · 2012: 78
FWCI: 8.37
Type: journal article
Language: en
Open access: closed
Locations: Journal of the American Statistical Association (publishedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
Physical Sciences › Mathematics › Statistics and Probability › Statistical Distribution Estimation and Applications
Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
Keywords: multivariate failure time data, marginal distributions, Cox proportional hazards model, asymptotic normality, simultaneous inference, time-varying covariates, missing data, censorship, recurrent events, dependence structure

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Regression Analysis of Multivariate Incomplete Failure Time Data by Modeling Marginal Distributions

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