A test of inflated zeros for Poisson regression models. (April 2019)

• Record Type: Journal Article
• Authors: He, Hua; Zhang, Hui; Ye, Peng; Tang, Wan
• Is Part Of: Statistical methods in medical research. Volume 28:Number 4(2019)
• Page Start: 1157
• Page End: 1169
• Publication Date: 2019-04
• Subjects: Zero-inflated Poisson (ZIP) -- hypothesis test -- Vuong test -- type I error -- power; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280217749991
• Languages: English
• ISSNs: 0962-2802

Abstract

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.