CONFIDENCE AND PREDICTION INTERVALS FOR GENERALISED LINEAR ACCIDENT MODELS

Generalised linear models, with "log" link and either Poisson or negative binomial errors, are commonly used for relating accident rates to explanatory variables. This paper adds to the toolkit for such models. It describes how confidence intervals (for example, for the true accident rate at given flows) and prediction intervals (for example, for the number of accidents at a new site with given flows) can be produced using spreadsheet technology. (A) "Reprinted with permission from Elsevier".

• Record URL:
  • http://www.sciencedirect.com/science/article/B6V5S-4DYW4P4-1/1/b33fbb4e56b7ae38be587bd187c70c41
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00014575
• Corporate Authors:

  Elsevier

  The Boulevard, Langford Lane
  Kidlington, Oxford  United Kingdom  OX5 1GB
• Authors:
  • WOOD, G R
• Publication Date: 2005-3

Language

• English

Media Info

• Features: References;
• Pagination: p. 267-73
• Serial:
  • Accident Analysis & Prevention
  • Volume: 37
  • Issue Number: 2
  • Publisher: Elsevier
  • ISSN: 0001-4575
  • Serial URL: http://www.sciencedirect.com/science/journal/00014575

Subject/Index Terms

• TRT Terms: Crashes; Errors; Poisson distributions; Poisson ratio; Simulation; Technology
• ITRD Terms: 1643: Accident; 6440: Error; 5924: Poisson's ratio; 9103: Simulation; 3855: Technology
• Subject Areas: Safety and Human Factors;

Filing Info

• Accession Number: 00987200
• Record Type: Publication
• Source Agency: Transport Research Laboratory
• Files: ITRD, ATRI
• Created Date: Mar 3 2005 12:00AM