2007
DOI: 10.1027/1614-2241.3.3.89
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Overdispersion in the Poisson Regression Model

Abstract: Abstract. This simulation study compares different strategies to solve the problem of underestimating standard errors in the Poisson regression model when overdispersion is present. The study analyses the importance of sample size, Poisson distribution mean, and dispersion parameter in choosing the best index or estimate. Results show that standard error (SE) estimates obtained by resampling (nonparametric bootstrap and jackknife) are the least biased, followed by the direct index based on the χ2, and the so-c… Show more

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Cited by 16 publications
(6 citation statements)
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References 33 publications
(49 reference statements)
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“…We did not observe ants on sprouts wider than 7 cm ( S1 Table ) [ 98 ]. The data from plants 40c-B and 89 were outliers (observations carried out in early morning), so were removed from the PMRM analysis [ 99 ]. Type III test of fixed model in PMRM showed that the inclusion of the cladode width was negatively associated with the number of ants on sprouts ( Table 1 ), that is, ants visited narrower cladodes more frequently.…”
Section: Resultsmentioning
confidence: 99%
“…We did not observe ants on sprouts wider than 7 cm ( S1 Table ) [ 98 ]. The data from plants 40c-B and 89 were outliers (observations carried out in early morning), so were removed from the PMRM analysis [ 99 ]. Type III test of fixed model in PMRM showed that the inclusion of the cladode width was negatively associated with the number of ants on sprouts ( Table 1 ), that is, ants visited narrower cladodes more frequently.…”
Section: Resultsmentioning
confidence: 99%
“…We performed the overdispersion test proposed by Cameron and Trivedi [2009, p. 575] and failed to reject the null hypothesis of no significant over dispersion (p value = 0.307). However, we estimate the regression using heteroskedasticity-consistent robust standard error to account for potential heterogeneity (arising, for example, from differences among the sizes of the observations, although most of the independent variables are measured in logarithmic form) that could be an additional source of overdispersion [Palmer et al, 2007].…”
Section: Econometric Methodsmentioning
confidence: 99%
“…Consequently, the accuracy of parameter and standard error estimates are undermined (e.g. Palmer et al, 2007). Although alternatives such as the quasi-likelihood methods have been proposed to tackle these problems, they only serve as partial solutions, and their finite sample performance can be unsatisfactory (Nelder and Lee, 1992).…”
Section: Introductionmentioning
confidence: 99%