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Joint modelling of event counts and survival times
Author(s) -
Cowling B. J.,
Hutton J. L.,
Shaw J. E. H.
Publication year - 2006
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/j.1467-9876.2005.00529.x
Subject(s) - covariate , event (particle physics) , counting process , event data , survival analysis , poisson distribution , statistics , joint (building) , computer science , count data , econometrics , mathematics , engineering , physics , quantum mechanics , architectural engineering
Summary. 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.