title: Modelling recurrent events: a tutorial for analysis in epidemiology.
abstract: 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.
authors.affiliation: Department of Statistics, Institute of Mathematics, Federal University of Bahia, Brazil and Department of Biostatistics, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA leiladen@ufba.br.
authors.forename: Leila D A F
authors.initials: LD
authors.lastname: Amorim
authors.affiliation: Department of Statistics, Institute of Mathematics, Federal University of Bahia, Brazil and Department of Biostatistics, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
authors.forename: Jianwen
authors.initials: J
authors.lastname: Cai
mesh_terms: D000465:Algorithms; D015982:Bias; D003627:Data Interpretation, Statistical; D004812:Epidemiologic Methods; D016021:Epidemiologic Studies; D006801:Humans; D015233:Models, Statistical
keywords: Recurrent events; survival modelling; time-to-event data