Joint modeling of recurrent events and a terminal event adjusted for zero inflation and a matched design

Research output: Contribution to journalArticlepeer-review


In longitudinal studies, matched designs are often employed to control the potential confounding effects in the field of biomedical research and public health. Because of clinical interest, recurrent time-to-event data are captured during the follow-up. Meanwhile, the terminal event of death is always encountered, which should be taken into account for valid inference because of informative censoring. In some scenarios, a certain large portion of subjects may not have any recurrent events during the study period due to nonsusceptibility to events or censoring; thus, the zero-inflated nature of data should be considered in analysis. In this paper, a joint frailty model with recurrent events and death is proposed to adjust for zero inflation and matched designs. We incorporate 2 frailties to measure the dependency between subjects within a matched pair and that among recurrent events within each individual. By sharing the random effects, 2 event processes of recurrent events and death are dependent with each other. The maximum likelihood based approach is applied for parameter estimation, where the Monte Carlo expectation-maximization algorithm is adopted, and the corresponding R program is developed and available for public usage. In addition, alternative estimation methods such as Gaussian quadrature (PROC NLMIXED) and a Bayesian approach (PROC MCMC) are also considered for comparison to show our method's superiority. Extensive simulations are conducted, and a real data application on acute ischemic studies is provided in the end.

Original languageEnglish (US)
Pages (from-to)2771-2786
Number of pages16
JournalStatistics in Medicine
Issue number18
StatePublished - Aug 15 2018

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Statistics and Probability

Fingerprint Dive into the research topics of 'Joint modeling of recurrent events and a terminal event adjusted for zero inflation and a matched design'. Together they form a unique fingerprint.

Cite this