A varying-coefficient model for gap times between recurrent events

• Published in: Lifetime data analysis Vol. 27; no. 3; pp. 437 - 459
• Main Authors: Soh, J. E., Huang, Yijian
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.07.2021; Springer Nature B.V
• Subjects: Bladder; Bladder cancer; Coefficients; Economics; Finance; Health Sciences; Insurance; Management; Mathematics and Statistics; Medicine; Monte Carlo simulation; Operations Research/Decision Theory; Quality Control; Regression models; Reliability; Safety and Risk; Statistics; Statistics for Business; Statistics for Life Sciences; Time measurement; Event history analysis; Multivariate survival data; Marginal modeling; Multiplier bootstrap; Varying-effects model; Renewal Process
• ISSN: 1380-7870; 1572-9249; 1572-9249
• DOI: 10.1007/s10985-021-09523-7

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.