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epi.bohning

Bohning's test for overdispersion of Poisson data


Description

A test for overdispersion of Poisson data.

Usage

epi.bohning(obs, exp, alpha = 0.05)

Arguments

obs

the observed number of cases in each area.

exp

the expected number of cases in each area.

alpha

alpha level to be used for the test of significance. Must be a single number between 0 and 1.

Value

A data frame with two elements: test.statistic, Bohning's test statistic and p.value the associated P-value.

References

Bohning D (2000). Computer-assisted Analysis of Mixtures and Applications. Chapman and Hall, Boca Raton.

Ugarte MD, Ibanez B, Militino AF (2006). Modelling risks in disease mapping. Statistical Methods in Medical Research 15: 21 - 35.

Examples

data(epi.SClip)
obs <- epi.SClip$cases
pop <- epi.SClip$population
exp <- (sum(obs) / sum(pop)) * pop

epi.bohning(obs, exp, alpha = 0.05)

epiR

Tools for the Analysis of Epidemiological Data

v2.0.19
GPL (>= 2)
Authors
Mark Stevenson <mark.stevenson1@unimelb.edu.au> and Evan Sergeant <evansergeant@gmail.com> with contributions from Telmo Nunes, Cord Heuer, Jonathon Marshall, Javier Sanchez, Ron Thornton, Jeno Reiczigel, Jim Robison-Cox, Paola Sebastiani, Peter Solymos, Kazuki Yoshida, Geoff Jones, Sarah Pirikahu, Simon Firestone, Ryan Kyle, Johann Popp, Mathew Jay and Charles Reynard.
Initial release
2021-01-12

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