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7203459 
Journal Article 
GEE-based zero-inflated generalized Poisson model for clustered over or under-dispersed count data 
Sarvi, F; Moghimbeigi, A; Mahjub, H; , 
2019 
Yes 
Journal of Statistical Computation and Simulation
ISSN: 0094-9655
EISSN: 1563-5163 
TAYLOR & FRANCIS LTD 
ABINGDON 
2711-2732 
WOS:000473278300001 
The zero-inflated regression models such as zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB) or zero-inflated generalized Poisson (ZIGP) regression models can model the count data with excess zeros. The ZINB model can handle over-dispersed and the ZIGP model can handle the over or under-dispersed count data with excess zeros as well. Moreover, the count data may be correlated because of data collection procedure or special study design. The clustered sampling approach is one of the examples in which the correlation among subjects could be defined. In such situations, a marginal model using generalized estimating equation (GEE) approach can incorporate these correlations and lead up to the relationships at the population level. In this study, the GEE-based zero-inflated generalized Poisson regression model was proposed to fit over and under-dispersed clustered count data with excess zeros.