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Approaches to Modelling Overdispersion in the Analysis of Migration [PDF]

Environment and Planning A: Economy and Space, 1993
In this paper the modelling of overdispersion in generalised Poisson and multinomial models of migration flows and rates is considered, and its importance within the wider question of substantive model specification is shown. It is argued that substantive specification and the modelling of overdispersion are closely interrelated.
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Overdispersion

1999
Abstract Categorical data are produced when the response is an indicator of which of a number of events has occurred. However, these will be repeated measurements only if repeated events are observed on the same units (Section 1.2). When no explanatory variables, not even time, distinguish such responses on a unit, the events can be ...
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A Note on a Test for Poisson Overdispersion

Biometrika, 1994
SUMMARY This note discusses an error occurring in a test for Poisson overdispersion suggested by Tiago de Oliveira (1965). The limiting null distribution of the suggested statistic is neither pivotal nor is it standard normal. The error lies in the computation of the asymptotic standard error of the overdispersion estimate, for which a corrected ...
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Overdispersion and Poisson Regression

Journal of Quantitative Criminology, 2008
This article discusses the use of regression models for count data. A claim is often made in criminology applications that the negative binomial distribution is the conditional distribution of choice when for a count response variable there is evidence of overdispersion.
Richard Berk, John M. MacDonald
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Hypothesis Testing for Proportions with Overdispersion

Biometrics, 1986
The properties of likelihood ratio tests and simpler t-tests are investigated by simulation under an assumed beta-binomial model for parameter values typically found in toxicological studies. It is found that likelihood ratio methods are at least as powerful as the simpler approaches and in certain situations can be significantly more powerful.
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On modelling overdispersion of counts

Statistica Neerlandica, 1999
For counts it often occurs that the observed variance exceeds the nominal variance of the claimed binomial, multinomial or Poisson distributions. We study how models can be extended to cope with this phenomenon: a survey of literature is given. We focus on modelling, not on estimation or testing statistical hypotheses.
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Overdispersion in nuclear statistics

Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 1999
Abstract The modern statistical distribution theory is applied to the development of the overdispersion theory in ionizing-radiation statistics for the first time. The physical nuclear system is treated as a sequence of binomial processes, each depending on a characteristic probability, such as probability of decay, detection, etc.
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Overdispersion and cluster models

1995
Abstract As we have seen in previous chapters of this part, count data arise from the enumeration of events on individual units. If no explanatory variables, or time, distinguish among the events, they may be aggregated as counts. In fact, this can only be done legitimately for Poisson or binomial data if the events are independent.
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Overdispersion in poisson regression

2008
Investigation of a possible relationship between air quality and human health in the community of Prince George, British Columbia was undertaken after a public opinion poll in 1972 discovered that poor air quality was the number one concern of the residents of Prince George.
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overdispersed, adj.

2023
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