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Bootstrap tests for overdispersion in a zero-inflated Poisson regression model.

Byoung Cheol Jung·Myoungshic Jhun·Jae Won Lee
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Abstract

Ridout, Hinde, and Demétrio (2001, Biometrics 57, 219-223) derived a score test for testing a zero-inflated Poisson (ZIP) regression model against zero-inflated negative binomial (ZINB) alternatives. They mentioned that the score test using the normal approximation might underestimate the nominal significance level possibly for small sample cases. To remedy this problem, a parametric bootstrap method is proposed. It is shown that the bootstrap method keeps the significance level close to the nominal one and has greater power uniformly than the existing normal approximation for testing the hypothesis.

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BiometryComputer SimulationModels, StatisticalMonte Carlo MethodPlant RootsPoisson DistributionRegression AnalysisCommentJournal ArticleResearch Support, Non-U.S. Gov't

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Byoung Cheol Jung, Myoungshic Jhun, Jae Won Lee. 2005. Bootstrap tests for overdispersion in a zero-inflated Poisson regression model.. https://doi.org/10.1111/j.1541-0420.2005.00368.x

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