Poisson regression is a common approach for modelling discrete data. However, due to characteristics of distribution, might not be suitable since most data are over-dispersed or under-dispersed. This study compared four generalised linear models (GLMs): negative binomial, Poisson, zero-truncated and binomial. An air-pollution-related disease, upper respiratory tract infection (URTI), its relati...

Usual approaches for estimating the variance of a standardized rate may not be applicable to rates of recurrent events. Where individuals are prone to repeated health events, Greenwood and Yule (J R Stat Soc [A], 1920;83:255-79) advocated use of the negative binomial distribution to account for departures from the assumption of randomness of recurrent events required by the Poisson distribution...

Author Contact: Glen Roberts c/o David E. Giles, Dept. of Economics, University of Victoria, P.O. Box 1700, STN CSC, Victoria, B.C., V8W 2Y2, Canada; email: [email protected] (cc: [email protected]); FAX: (250) 721-6214 Abstract We model summer Olympic medal counts using count data analysis. The advantage of this methodology is its explicit recognition of the discrete non-negative form of the dependent...

Dengue Hemorrhagic Fever (DHF) is one of the diseases with unsual occurrence in Central Java and spread throughout regency/city. The number sufferers this disease still high because mortality rate above national target. Regarding less handling DHF spread, it necessary to make a plan by identify factors that allegedly affect case. Characteristics data cases count data, so research carried out us...

Materials and methods: Gilt and boar progeny from 8276 litters of a genetic multiplier that used four dam lines and fi ve sire lines were observed for umbilical hernias by 11 weeks of age. Hernias were attributed to birth litter. Odds of umbilical hernia development were calculated using logistic regression and rates were calculated using Poisson regression. Negative binomial models using sire ...

In a Poisson regression model, where observations are either clustered or represented by repeated measurements of counts, the number of observed zero counts is sometimes greater than the expected frequency by the Poisson distribution and the non-zero part of count data may be overdispersed. The zero-inflated negative binomial (ZINB) mixed regression model is suggested to analyze such data. Prev...

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 s...

In this paper, we discuss a generalization of the classical compound Poisson model with claim sizes following distribution. As applications, consider models involving zero-truncated geometric, negative-binomial and binomial batch-claim arrivals. We also provide some ruin-related quantities under resulting risk models. Finally, through numerical examples, visualize behavior these quantities.