
pmid: 26686485
The purpose of this article is to make the standard promotion cure rate model (Yakovlev and Tsodikov, ) more flexible by assuming that the number of lesions or altered cells after a treatment follows a fractional Poisson distribution (Laskin, ). It is proved that the well‐known Mittag‐Leffler relaxation function (Berberan‐Santos, ) is a simple way to obtain a new cure rate model that is a compromise between the promotion and geometric cure rate models allowing for superdispersion. So, the relaxed cure rate model developed here can be considered as a natural and less restrictive extension of the popular Poisson cure rate model at the cost of an additional parameter, but a competitor to negative‐binomial cure rate models (Rodrigues et al., ). Some mathematical properties of a proper relaxed Poisson density are explored. A simulation study and an illustration of the proposed cure rate model from the Bayesian point of view are finally presented.
geometric cure rate model, Likelihood Functions, Models, Statistical, Poisson cure rate model, Bayesian inference, Bayes Theorem, Applications of statistics to biology and medical sciences; meta analysis, Treatment Outcome, Recurrence, Neoplasms, relaxed Poisson cure rate model, Humans, Mittag-Leffler relaxation function, Poisson Distribution, fractional Poisson distribution
geometric cure rate model, Likelihood Functions, Models, Statistical, Poisson cure rate model, Bayesian inference, Bayes Theorem, Applications of statistics to biology and medical sciences; meta analysis, Treatment Outcome, Recurrence, Neoplasms, relaxed Poisson cure rate model, Humans, Mittag-Leffler relaxation function, Poisson Distribution, fractional Poisson distribution
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