The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Some remarks on overdispersion
Abstract
It is shown that maximum likelihood estimation of a simple model retains high efficiency in the presence of modest amounts of overdispersion. The main requirement is that the target parameter should be the moment parameter of an exponential family distribution, or more generally of a parameter for which the order n−1 bias of the maximum likelihood estimate is zero. Extensions for models with explanatory variables are outlined.
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Citations
Cites
Quasi-likelihood functions, generalized linear models, and the Gauss—Newton method
WEDDERBURN, R. W. M. (1974) · Biometrika · doi:10.1093/biomet/61.3.439 · Cited by 2,122
Cited by
Specification and testing of some modified count data models
Mullahy, J. (1986) · Journal of Econometrics · doi:10.1016/0304-4076(86)90002-3 · Cited by 1,870
Econometric models based on count data. Comparisons and applications of some estimators and tests
Cameron, A. C., & Trivedi, P. K. (1986) · Journal of Applied Econometrics · doi:10.1002/jae.3950010104 · Cited by 1,771
Regression-based tests for overdispersion in the Poisson model
Cameron, A. C., & Trivedi, P. K. (1990) · Journal of Econometrics · doi:10.1016/0304-4076(90)90014-k · Cited by 1,192
Miaou, S.-P. (1994) · Accident Analysis & Prevention · doi:10.1016/0001-4575(94)90038-8 · Cited by 770
Model Robust Confidence Intervals Using Maximum Likelihood Estimators
Royall, R. M. (1986) · International Statistical Review / Revue Internationale de Statistique · doi:10.2307/1403146 · Cited by 578
Metadata
- Authors
- COX, D. R.
- Venue
- Biometrika
- Publisher
- Oxford University Press (OUP)
- Published
- 1983
- Volume
- 70
- Issue
- 1
- Pages
- 269-274
- ISSN
- 0006-3444 (ISSN-L)
- 1464-3510
- OpenAlex
- W1982142842
- Cited by
- 521
- References
- 1
- FWCI
- 5.84
- Type
- journal article
- Language
- en
- Open access
- closed
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