A Score Test for Testing a Marginalized Zero-Inflated Poisson Regression Model Against a Marginalized Zero-Inflated Negative Binomial Regression Model |
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Authors: | Gul Inan John Preisser Kalyan Das |
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Affiliation: | 1.Department of Statistics,Middle East Technical University,Ankara,Turkey;2.Department of Biostatistics,University of North Carolina,Chapel Hill,USA;3.Department of Statistics,University of Calcutta,Kolkata,India |
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Abstract: | Marginalized zero-inflated count regression models (Long et al. in Stat Med 33(29):5151–5165, 2014) provide direct inference on overall exposure effects. Unlike standard zero-inflated models, marginalized models specify a regression model component for the marginal mean in addition to a component for the probability of an excess zero. This study proposes a score test for testing a marginalized zero-inflated Poisson model against a marginalized zero-inflated negative binomial model for model selection based on an assessment of over-dispersion. The sampling distribution and empirical power of the proposed score test are investigated via a Monte Carlo simulation study, and the procedure is illustrated with data from a horticultural experiment. Supplementary materials accompanying this paper appear on-line. |
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