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A test for overdispersion of Poisson data.
epi.bohning(obs, exp, alpha = 0.05)
the observed number of cases in each area.
the expected number of cases in each area.
alpha level to be used for the test of significance. Must be a single number between 0 and 1.
A data frame with two elements: test.statistic, Bohning's test statistic and p.value the associated P-value.
test.statistic
p.value
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.
data(epi.SClip) obs <- epi.SClip$cases pop <- epi.SClip$population exp <- (sum(obs) / sum(pop)) * pop epi.bohning(obs, exp, alpha = 0.05)
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