The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A general maximum likelihood analysis of overdispersion in generalized linear models
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Citations
Cites
McCullagh, P., & Nelder, J. A. (1989) · doi:10.1007/978-1-4899-3242-6 · Cited by 16,836
Nonparametric maximum likelihood estimation of a mixing distribution
Laird, N. (1978) · Journal of the American Statistical Association · doi:10.1080/01621459.1978.10480103 · Cited by 753
Cited by
A comparison of Bayesian and likelihood-based methods for fitting multilevel models
Browne, W. J., & Draper, D. (2006) · Bayesian Analysis · doi:10.1214/06-ba117 · Cited by 603
A General Maximum Likelihood Analysis of Variance Components in Generalized Linear Models
Aitkin, M. (1999) · Biometrics · doi:10.1111/j.0006-341x.1999.00117.x · Cited by 398
Self-citationKarlis, D., & Xekalaki, E. (2007) · International Statistical Review · doi:10.1111/j.1751-5823.2005.tb00250.x · Cited by 324
Trends in quantitative methods I: stressing the local
Fotheringham, A. S. (1997) · Progress in Human Geography · doi:10.1191/030913297676693207 · Cited by 276
Metadata
- Authors
- Aitkin, M.
- Venue
- Statistics and Computing
- Published
- 1996-09
- Volume
- 6
- Issue
- 3
- Pages
- 251-262
- ISSN
- 0960-3174 (ISSN-L)
- 1573-1375
- OpenAlex
- W2053633338
- Cited by
- 200
- References
- 2
- FWCI
- 8.31
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A general maximum likelihood analysis of overdispersion in generalized linear models. https://app.cochat.ai/papers/10.1007/bf00140869
- The paper
- Aitkin, M. (1996). A general maximum likelihood analysis of overdispersion in generalized linear models. Statistics and Computing. https://doi.org/10.1007/bf00140869
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
