A Score Test for Testing a Marginalized Zero-Inflated Poisson Regression Model Against a Marginalized Zero-Inflated Negative Binomial Regression Model

Inan G., Preisser J., Das K.

JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS, vol.23, no.1, pp.113-128, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 23 Issue: 1
  • Publication Date: 2018
  • Doi Number: 10.1007/s13253-017-0314-5
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.113-128
  • Keywords: Count data, Excess zeros, Marginal models, Over-dispersion, Score test, DENTAL-CARIES INDEXES, MIXED MODELS, OVERDISPERSION
  • Middle East Technical University Affiliated: Yes


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.