Journal
BIOMETRIKA
Volume 96, Issue 2, Pages 293-306Publisher
OXFORD UNIV PRESS
DOI: 10.1093/biomet/asp005
Keywords
Accelerated failure time model; Asymptotic normality; Correlated survival data; Estimation efficiency; Moment condition; Rank estimation; Semiparametric model
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We propose a generalized method of moments approach to the accelerated failure time model with correlated survival data. We study the semiparametric rank estimator using martingale-based moments. We circumvent direct estimation of correlation parameters by concatenating the moments and minimizing a quadratic objective function. We establish the consistency and asymptotic normality of the parameter estimators, and derive the limiting distribution of the objective function. We carry out simulation studies to examine the finite-sample properties of the method, and demonstrate its substantial efficiency gain over the conventional method. Finally, we illustrate the new proposal with an example from a diabetic retinopathy study.
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