Modelling recurrent events: a tutorial for analysis in epidemiology
Open accessAbstract
In many biomedical studies, the event of interest can occur more than once in a participant. These events are termed recurrent events. However, the majority of analyses focus only on time to the first event, ignoring the subsequent events. Several statistical models have been proposed for analysing multiple events. In this paper we explore and illustrate several modelling techniques for analysis of recurrent time-to-event data, including conditional models for multivariate survival data (AG, PWP-TT and PWP-GT), marginal means/rates models, frailty and multi-state models. We also provide a tutorial for analysing such type of data, with three widely used statistical software programmes. Different approaches and software are illustrated using data from a bladder cancer project and from a study on lower respiratory tract infection in children in Brazil. Finally, we make recommendations for modelling strategy selection for analysis of recurrent event data.
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Prentice-Williams-Peterson regression is recommended when occurrence of the first event increases the likelihood of subsequent events.
“This stratified approach enables each event recurrence to have a distinct baseline hazard and is recommended when occurrence of the first event increases the likelihood of subsequent events.31”
From Factors associated with recurrent emergency department visits among people living with dementia: A retrospective cohort study (2023) · cites this paper as [31]
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- Authors
- Amorim, L. D., & Cai, J.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- ORCID
- Cai, Jianwen
- Venue
- International Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-12-09
- Volume
- 44
- Issue
- 1
- Pages
- 324-333
- ISSN
- 0300-5771 (ISSN-L)
- 1464-3685
- PMC
- PMC4339761
- OpenAlex
- W2102630933
- Cited by
- 564
- References
- 30
- Citations by year
- 2026: 57 · 2025: 84 · 2024: 53 · 2023: 76 · 2022: 63 · 2021: 58 · 2020: 53 · 2019: 58 · 2018: 33 · 2017: 13 · 2016: 10 · 2015: 5
- FWCI
- 9.87
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- International Journal of Epidemiology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- UNC Libraries
- Funders
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- National Institutes of Health (CA 142538)
- U.S. Public Health Service (ULIRR025747)
- National Cancer Institute (P01CA142538)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- recurrent events, multivariate survival models, frailty models, multi-state models, bladder cancer
- MeSH terms
- Algorithms, Data Interpretation, Statistical, Epidemiologic Methods, Humans, Models, Statistical, Bias, Epidemiologic Studies
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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