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June 2020 Generalized accelerated recurrence time model in the presence of a dependent terminal event
Bo Wei, Zhumin Zhang, HuiChuan J. Lai, Limin Peng
Ann. Appl. Stat. 14(2): 956-976 (June 2020). DOI: 10.1214/20-AOAS1335


Recurrent events are commonly encountered in longitudinal studies. The observation of recurrent events is often stopped by a dependent terminal event in practice. For this data scenario, we propose two sensible adaptations of the generalized accelerated recurrence time (GART) model (J. Amer. Statist. Assoc. 111 (2016) 145–156) to provide useful alternative analyses that can offer physical interpretations while rendering extra flexibility beyond the existing work based on the accelerated failure time model. Our modeling strategies align with the rationale underlying the use of the survivors’ rate function or the adjusted rate function to account for the presence of the dependent terminal event. For the proposed models, we identify and develop estimation and inference procedures which can be readily implemented based on existing software. We establish the asymptotic properties of the new estimator. Simulation studies demonstrate good finite-sample performance of the proposed methods. An application to a dataset from the Cystic Fibrosis Foundation Patient Registry (CFFPR) illustrates the practical utility of the new methods.


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Bo Wei. Zhumin Zhang. HuiChuan J. Lai. Limin Peng. "Generalized accelerated recurrence time model in the presence of a dependent terminal event." Ann. Appl. Stat. 14 (2) 956 - 976, June 2020.


Received: 1 July 2019; Revised: 1 January 2020; Published: June 2020
First available in Project Euclid: 29 June 2020

zbMATH: 07239891
MathSciNet: MR4117836
Digital Object Identifier: 10.1214/20-AOAS1335

Rights: Copyright © 2020 Institute of Mathematical Statistics


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Vol.14 • No. 2 • June 2020
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