An empirical approach to determine a threshold for assessing overdispersion in Poisson and negative binomial models for count data

Overdispersion is a problem encountered in the analysis of count data that can lead to invalid inference if unaddressed. Decision about whether data are overdispersed is often reached by checking whether the ratio of the Pearson chi-square statistic to its degrees of freedom is greater than one; how...

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Bibliographic Details
Published in:	Communications in statistics. Simulation and computation Vol. 47; no. 6; pp. 1722 - 1738
Main Authors:	Payne, Elizabeth H., Gebregziabher, Mulugeta, Hardin, James W., Ramakrishnan, Viswanathan, Egede, Leonard E.
Format:	Journal Article
Language:	English
Published:	United States Taylor & Francis 05.07.2018 Taylor & Francis Ltd
Subjects:	62Fxx Chi-square test Computer simulation Count data Datasets Economic models Empirical analysis outliers Outliers (statistics) overdispersion Pearson chi-square Statistical analysis Statistical tests zero inflation Count data 62Fxx outliers Pearson chi-square overdispersion 62J12 zero inflation
ISSN:	0361-0918, 1532-4141
Online Access:	Get full text
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