A test of inflated zeros for Poisson regression models

Hua He, Hui Zhang, Peng Ye, Wan Tang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Excessive zeros are common in practice and may cause overdispersion and invalidate inference when fitting Poisson regression models. There is a large body of literature on zero-inflated Poisson models. However, methods for testing whether there are excessive zeros are less well developed. The Vuong test comparing a Poisson and a zero-inflated Poisson model is commonly applied in practice. However, the type I error of the test often deviates seriously from the nominal level, rendering serious doubts on the validity of the test in such applications. In this paper, we develop a new approach for testing inflated zeros under the Poisson model. Unlike the Vuong test for inflated zeros, our method does not require a zero-inflated Poisson model to perform the test. Simulation studies show that when compared with the Vuong test our approach not only better at controlling type I error rate, but also yield more power.

Original languageEnglish (US)
Pages (from-to)1157-1169
Number of pages13
JournalStatistical Methods in Medical Research
Issue number4
StatePublished - Apr 1 2019


  • Vuong test
  • Zero-inflated Poisson (ZIP)
  • hypothesis test
  • power
  • type I error

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability
  • Health Information Management


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