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Joint modelling of event counts and survival times

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In studies of recurrent events, such as epileptic seizures, there can be a large amount of information about a cohort over a period of time, but current methods for these data are often unable to utilize all of the available information. The paper considers data which include post-treatment survival times for individuals experiencing recurring events, as well as a measure of the base-line event rate, in the form of a pre-randomization event count. Standard survival analysis may treat this pre-randomization count as a covariate, but the paper proposes a parametric joint model based on an underlying Poisson process, which will give a more precise estimate of the treatment effect.

Keywords: Censored point process; Epilepsy; Event rate; Recurrent event; Survival analysis

Document Type: Research Article


Affiliations: 1: University of Hong Kong, Pokfulam, People's Republic of China 2: University of Warwick, Coventry, UK

Publication date: January 1, 2006


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