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

The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.

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
Open this paper in CoChat — free account

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.

Overview

Integrity signals

Registry

Crossref · 10.1080/01621459.1989.10478873

Cites

31 of 31 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Show all 31 references

Research works printed but not linked: 2

  1. Gill R. D., 1980, Censoring and Stochastic Integrals (Tract 124)
  2. Hougaard P., 1986, Biometrika, 73, 671

Cited by

Sorted by citations

See all 1,868

Related

Metadata

Authors
Wei, L. J., Lin, D. Y., & Weissfeld, L.
Affiliations
  • University of Wisconsin–Madison (US)
  • Harvard University (US)
  • University of Michigan (US)
ORCID
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

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review