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A score test for zero‐inflation in correlated count data
Author(s) -
Xiang Liming,
Lee Andy H.,
Yau Kelvin K. W.,
McLachlan Geoffrey J.
Publication year - 2005
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.2308
Subject(s) - count data , statistics , poisson distribution , poisson regression , statistic , inflation (cosmology) , mathematics , zero (linguistics) , test statistic , data set , range (aeronautics) , score test , cluster sampling , econometrics , statistical hypothesis testing , medicine , physics , population , linguistics , philosophy , environmental health , materials science , theoretical physics , composite material
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. Copyright © 2005 John Wiley & Sons, Ltd.