A varying-coefficient model for gap times between recurrent events

J. E. Soh () and Yijian Huang ()
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J. E. Soh: Emory University
Yijian Huang: Emory University

Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, 2021, vol. 27, issue 3, No 5, 437-459

Abstract: Abstract Recurrent events often arise in follow-up studies where a subject may experience multiple occurrences of the same type of event. Most regression models for recurrent events consider the time scale measured from the study origin and assume constant effects of covariates. In many applications, however, gap times between recurrent events are of natural interest and moreover the effects may actually vary over time. In this article, we propose a marginal varying-coefficient model for gap times between recurrent events that allows for the intra-individual correlation between events. Estimation and inference procedures are developed for the varying coefficients. Consistency and weak convergence of the proposed estimator are established. Monte Carlo simulation studies demonstrate that the proposed method works well with practical sample sizes. The proposed method is illustrated with an analysis of bladder tumor clinical data.

Keywords: Event history analysis; Marginal modeling; Multiplier bootstrap; Multivariate survival data; Renewal Process; Varying-effects model (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s10985-021-09523-7

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