Linear Regression Analysis for Multivariate Failure Time Observations
作者:
J.S. Lin,
L.J. Wei,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1992)
卷期:
Volume 87,
issue 420
页码: 1091-1097
ISSN:0162-1459
年代: 1992
DOI:10.1080/01621459.1992.10476264
出版商: Taylor & Francis Group
关键词: Buckley–James procedure;Estimating equation;Multistage multiple inference method;Rank statistics;Weighted partial likelihood score function
数据来源: Taylor
摘要:
In this article we consider the case that each patient in a longitudinal study may experience two or more distinct failures. The corresponding failure times, which are possible censored, are recorded for each patient. The logarithm of each marginal failure time is assumed to be linearly related to its covariates; however, the distributional form of the error term in the model does not have to be specified in the analysis. Furthermore, no specific structure of dependence among the distinct failure times on each subject has to be imposed. Various linear regression methods for analyzing multivariate failure time observations are proposed. Our procedures do not involve the unstable nonparametric hazard function estimation. Extensive numerical studies are conducted to evaluate the new proposals. Recommendations are also made for their practical usage.
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