title: A score test for zero-inflation in correlated count data.
abstract: To account for the preponderance of zero counts and simultaneous correlation of observations, a class of zero-inflated Poisson mixed regression models is applicable for accommodating the within-cluster dependence. In this paper, a score test for zero-inflation is developed for assessing correlated count data with excess zeros. The sampling distribution and the power of the test statistic are evaluated by simulation studies. The results show that the test statistic performs satisfactorily under a wide range of conditions. The test procedure is further illustrated using a data set on recurrent urinary tract infections.
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Curtin University of Technology, G.P.O. Box U 1987, Perth, WA 6845, Australia.
authors.forename: Liming
authors.initials: L
authors.lastname: Xiang
authors.forename: Andy H
authors.initials: AH
authors.lastname: Lee
authors.forename: Kelvin K W
authors.initials: KK
authors.lastname: Yau
authors.forename: Geoffrey J
authors.initials: GJ
authors.lastname: McLachlan
mesh_terms: D000368:Aged; D015331:Cohort Studies; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005260:Female; D006707:Homes for the Aged; D006801:Humans; D008875:Middle Aged; D008954:Models, Biological; D015233:Models, Statistical; D016012:Poisson Distribution; D012189:Retrospective Studies; D012307:Risk Factors; D014552:Urinary Tract Infections / Q000453:epidemiology