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Extended P oisson process modelling and analysis of grouped binary data
Author(s) -
Faddy Malcolm J.,
Smith David M.
Publication year - 2012
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.201100214
Subject(s) - poisson distribution , mathematics , dispersion (optics) , negative binomial distribution , binary data , index of dispersion , binomial distribution , statistics , count data , interval (graph theory) , extension (predicate logic) , probability distribution , quasi likelihood , binary number , computer science , poisson regression , combinatorics , population , physics , demography , arithmetic , sociology , optics , programming language
A simple extension of the P oisson process results in binomially distributed counts of events in a time interval. A further extension generalises this to probability distributions under‐ or over‐dispersed relative to the binomial distribution. Substantial levels of under‐dispersion are possible with this modelling, but only modest levels of over‐dispersion – up to P oisson‐like variation. Although simple analytical expressions for the moments of these probability distributions are not available, approximate expressions for the mean and variance are derived, and used to re‐parameterise the models. The modelling is applied in the analysis of two published data sets, one showing under‐dispersion and the other over‐dispersion. More appropriate assessment of the precision of estimated parameters and reliable model checking diagnostics follow from this more general modelling of these data sets.