A score test for overdispersion in zero-inflated poisson mixed regression model.
Count data with extra zeros are common in many medical applications. The zero-inflated Poisson (ZIP) regression model is useful to analyse such data. For hierarchical or correlated count data where the observations are either clustered or represent repeated outcomes from individual subjects, a class of ZIP mixed regression models may be appropriate. However, the ZIP parameter estimates can be severely biased if the non-zero counts are overdispersed in relation to the Poisson distribution. In this paper, a score test is proposed for testing the ZIP mixed regression model against the zero-inflated negative binomial alternative. Sampling distribution and 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 applied to pancreas disorder length of stay that comprised mainly same-day separations and simultaneous prolonged hospitalizations.
Xiang
Liming
L
Department of Management Sciences, City University of Hong Kong, Kowloon.
Lee
Andy H
AH
Yau
Kelvin K W
KK
McLachlan
Geoffrey J
GJ
D000328:Adult; D016010:Binomial Distribution; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D007902:Length of Stay; D008297:Male; D010182:Pancreatic Diseases / Q000628:therapy; D016012:Poisson Distribution; D012044:Regression Analysis; D014904:Western Australia