The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
A comprehensive methodology for the fitting of predictive accident models
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Citations
Cites
(2005) · Statistics for Biology and Health · doi:10.1007/0-387-27255-0_9 · Cited by 20,133
Information Theory and an Extension of the Maximum Likelihood Principle
Akaike, H. (1998) · Springer Series in Statistics · doi:10.1007/978-1-4612-1694-0_15 · Cited by 17,781
Quasi-likelihood functions, generalized linear models, and the gauss-newton method
Wedderburn, R. W. M. (1974) · Biometrika · doi:10.2307/2334725 · Cited by 2,122
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
McCullagh, P., & Nelder, J. A. (1983) · Springer eBooks · doi:10.1007/978-1-4899-3244-0 · Cited by 1,980
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
Miaou, S.-P. (1994) · Accident Analysis & Prevention · doi:10.1016/0001-4575(94)90038-8 · Cited by 770
Collett, D., Baker, R. J., & Nelder, J. A. (1979) · Biometrics · doi:10.2307/2530359 · Cited by 645
Modeling vehicle accidents and highway geometric design relationships
Miaou, S.-P., & Lum, H. (1993) · Accident Analysis & Prevention · doi:10.1016/0001-4575(93)90034-t · Cited by 536
Estimating truck accident rate and involvements using linear and Poisson regression models
Joshua, S. C., & Garber, N. J. (1990) · Transportation Planning and Technology · doi:10.1080/03081069008717439 · Cited by 266
Cited by
Lord, D., & Mannering, F. (2010) · Transportation Research Part A: Policy and Practice · doi:10.1016/j.tra.2010.02.001 · Cited by 1,759
A note on modeling vehicle accident frequencies with random-parameters count models
Anastasopoulos, P. C., & Mannering, F. L. (2009) · Accident Analysis & Prevention · doi:10.1016/j.aap.2008.10.005 · Cited by 688
Accident prediction models for urban roads
Greibe, P. (2003) · Accident Analysis & Prevention · doi:10.1016/s0001-4575(02)00005-2 · Cited by 340
Lord, D., Guikema, S. D., & Geedipally, S. R. (2008) · Accident Analysis & Prevention · doi:10.1016/j.aap.2007.12.003 · Cited by 260
Predicting motor vehicle collisions using Bayesian neural network models: An empirical analysis
Xie, Y., Lord, D., & Zhang, Y. (2007) · Accident Analysis & Prevention · doi:10.1016/j.aap.2006.12.014 · Cited by 253
Metadata
- Authors
- Maher, M. J., & Summersgill, I.
- Venue
- Accident Analysis & Prevention
- Publisher
- Elsevier BV
- Published
- 1996-05
- Volume
- 28
- Issue
- 3
- Pages
- 281-296
- ISSN
- 0001-4575 (ISSN-L)
- OpenAlex
- W1964744847
- Cited by
- 282
- References
- 13
- FWCI
- 27.18
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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How to cite
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- CoChat. (2026). Citation check: A comprehensive methodology for the fitting of predictive accident models. https://app.cochat.ai/papers/10.1016/0001-4575(95)00059-3
- The paper
- Maher, M. J., & Summersgill, I. (1996). A comprehensive methodology for the fitting of predictive accident models. Accident Analysis & Prevention. https://doi.org/10.1016/0001-4575(95)00059-3
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.
