Modelling count data with excessive zeros: the need for class prediction in zero-inflated models and the issue of data generation in choosing between zero-inflated and generic mixture models for dental caries data.

Abstract

Count data may possess an 'excess' of zeros relative to standard distributions. Zero-inflated Poisson (ZiP) or binomial (ZiB) and generic mixture models have been proposed to deal with such data. We consider biomedical count data with an excess number of zeros and seek to address the following: (i) do zero-inflated models need covariates in the distribution… (More)
DOI: 10.1002/sim.3699

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