Mean and Variance Modeling of Under-Dispersed and Over-Dispersed Grouped Binary Data

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Authors Douglas M. Smith, Malcolm J. Faddy
Journal/Conference Name Journal of Statistical Software
Paper Category
Paper Abstract This article describes the R package BinaryEPPM and its use in determining maximum likelihood estimates of the parameters of extended Poisson process models for grouped binary data. These provide a Poisson process family of flexible models that can handle unlimited under-dispersion but limited over-dispersion in such data, with the binomial distribution being a special case. Within BinaryEPPM, models with the mean and variance related to covariates are constructed to match a generalized linear model formulation. Combining such under-dispersed models with standard over-dispersed models such as the beta binomial distribution provides a very general form of residual distribution for modeling grouped binary data. Use of the package is illustrated by application to several data-sets.
Date of publication 2019
Code Programming Language R

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