Joint modelling of event counts and survival times

• Published in: Applied statistics 2006-01, Vol.55 (1), p.31-39
• Main Authors: Cowling, B. J., Hutton, J. L., Shaw, J. E. H.
• Format: Article
• Language: English
• Subjects: Applications; Binomials; Censored point process; Data analysis; Epilepsy; Event rate; Exact sciences and technology; Global analysis, analysis on manifolds; Illness; Mathematics; Maximum likelihood estimation; Medical research; Methodology; Modeling; Nonparametric inference; Parametric models; Poisson process; Probability and statistics; Random allocation; Randomized algorithms; Recurrent event; Regression coefficients; Sciences and techniques of general use; Seizures; Standard error; Statistical analysis; Statistical methods; Statistical models; Statistics; Studies; Survival; Survival analysis; Topology. Manifolds and cell complexes. Global analysis and analysis on manifolds
• ISSN: 0035-9254; 1467-9876
• DOI: 10.1111/j.1467-9876.2005.00529.x

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.