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

作者：Inan Gul; Preisser John; Das Kalyan

来源：Journal of Agricultural, Biological, and Environmental Statistics, 2018, 23(1): 113-128.

DOI：10.1007/s13253-017-0314-5

• Count data
• Excess zeros
• Marginal models
• Over-dispersion
• Score test

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.

• 出版日期2018-3