QUASI-POISSON VS. NEGATIVE BINOMIAL REGRESSION: HOW SHOULD WE MODEL OVERDISPERSED COUNT DATA?
Top Cited Papers
- 1 November 2007
- Vol. 88 (11), 2766-2772
- https://doi.org/10.1890/07-0043.1
Abstract
No abstract availableKeywords
This publication has 19 references indexed in Scilit:
- Generalized Poisson Distribution: the Property of Mixture of Poisson and Comparison with Negative Binomial DistributionBiometrical Journal, 2005
- Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theoryAccident Analysis & Prevention, 2005
- THE ABUNDANCE OF HARBOR SEALS IN THE GULF OF ALASKAMarine Mammal Science, 2003
- Spatial modelling of individual-level parasite counts using the negative binomial distributionBiostatistics, 2000
- MONITORING THE TREND OF HARBOR SEALS IN PRINCE WILLIAM SOUND, ALASKA, AFTER THE EXXON VALDEZ OIL SPILLMarine Mammal Science, 1999
- Regression analyses of counts and rates: Poisson, overdispersed Poisson, and negative binomial models.Psychological Bulletin, 1995
- Zero-Inflated Poisson Regression, with an Application to Defects in ManufacturingTechnometrics, 1992
- A note on overdispersed exponential familiesBiometrika, 1990
- Double Exponential Families and Their Use in Generalized Linear RegressionJournal of the American Statistical Association, 1986
- Appraising Variability in Population StudiesThe Journal of Wildlife Management, 1978