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Estimated Pseudopartial‐Likelihood Method for Correlated Failure Time Data with Auxiliary Covariates
Author(s) -
Liu Yanyan,
Zhou Haibo,
Cai Jianwen
Publication year - 2009
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.1541-0420.2009.01198.x
Subject(s) - covariate , estimator , computer science , multivariate statistics , statistics , data set , statistical inference , inference , econometrics , set (abstract data type) , data mining , mathematics , artificial intelligence , programming language
Summary As biological studies become more expensive to conduct, statistical methods that take advantage of existing auxiliary information about an expensive exposure variable are desirable in practice. Such methods should improve the study efficiency and increase the statistical power for a given number of assays. In this article, we consider an inference procedure for multivariate failure time with auxiliary covariate information. We propose an estimated pseudopartial likelihood estimator under the marginal hazard model framework and develop the asymptotic properties for the proposed estimator. We conduct simulation studies to evaluate the performance of the proposed method in practical situations and demonstrate the proposed method with a data set from the studies of left ventricular dysfunction (SOLVD Investigators, 1991, New England Journal of Medicine 325 , 293–302).