A Score Test for Zero-Inflation in Correlated Count Data

Xiang, Liming, Lee, Andy H., Yau, Kelvin K. W. and McLachlan, Geoffrey J. (2006) A Score Test for Zero-Inflation in Correlated Count Data. Statistics In Medicine, 25 10: 1660-1671.


Author Xiang, Liming
Lee, Andy H.
Yau, Kelvin K. W.
McLachlan, Geoffrey J.
Title A Score Test for Zero-Inflation in Correlated Count Data
Journal name Statistics In Medicine   Check publisher's open access policy
ISSN 0277-6715
Publication date 2006-05-30
Sub-type Article (original research)
DOI 10.1002/sim.2308
Volume 25
Issue 10
Start page 1660
End page 1671
Total pages 12
Editor R D'Agonstino
Place of publication Chichester
Publisher John Wiley & Sons Ltd
Collection year 2006
Language eng
Subject C1
230204 Applied Statistics
230203 Statistical Theory
780101 Mathematical sciences
0104 Statistics
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. Copyright (c) 2005 John Wiley & Sons, Ltd.
Keyword Statistics & Probability
Public, Environmental & Occupational Health
Medical Informatics
Medicine, Research & Experimental
Count Data
Poisson Mixed Model
Power
Score Test
Zero-inflation
Poisson Regression
Models
Alternatives
Q-Index Code C1
Additional Notes DOI: 10.1002/sim.2308

 
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