A quasi-likelihood approach for ordered categorical data with overdispersion

Wang, Y-G. (1996) A quasi-likelihood approach for ordered categorical data with overdispersion. Biometrics, 52(4), pp. 1252-1258.

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Abstract

Quasi-likelihood (QL) methods are often used to account for overdispersion in categorical data. This paper proposes a new way of constructing a QL function that stems from the conditional mean-variance relationship. Unlike traditional QL approaches to categorical data, this QL function is, in general, not a scaled version of the ordinary log-likelihood function. A simulation study is carried out to examine the performance of the proposed QL method. Fish mortality data from quantal response experiments are used for illustration.

Impact and interest:

8 citations in Scopus
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7 citations in Web of Science®

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ID Code: 90625
Item Type: Journal Article
Refereed: Yes
Additional Information: ISI Document Delivery No.: VX804
Times Cited: 7
Cited Reference Count: 16
Wang, YG
International biometric soc
Washington
Keywords: categorical data, conditional likelihood, estimating equations, generalized linear models, overdispersion, quantal response, quasi-likelihood, toxicological mortality data, extra-binomial variation, linear-models, time
DOI: 10.2307/2532841
ISSN: 0006-341X
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: © 1996 International Biometric Society
Deposited On: 24 Nov 2015 04:09
Last Modified: 24 Nov 2015 04:09

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