Investigating Goodness-of-Fit Test Statistics for Generalized Linear Crash Models with Low Mean Values

This study has two objectives. The first objective is to examine the accuracy and reliability of test statistics for goodness-of-fit of generalized liner crash models under low crash mean situations. The second objective intends to identify a superior test statistic for goodness-of-fit tests. The Poisson and Poisson-Gamma models are commonly used to analyze crash data. For Poisson models, this paper proposes a better test statistic that can be applied for almost all mean values, except when the mean value is extremely low, for which no test statistic can be accurate. This statistic is also rather simple and easy to use. For Poisson-Gamma models, this study finds that traditional test statistics are not accurate and robust, and a more complicated method proposed in a past study is recommended. For better illustrations, real-world data are applied to identify and analyze the performances of different test statistics.

Language

  • English

Media Info

  • Media Type: CD-ROM
  • Features: Figures; References; Tables;
  • Pagination: 27p
  • Monograph Title: TRB 86th Annual Meeting Compendium of Papers CD-ROM

Subject/Index Terms

Filing Info

  • Accession Number: 01042553
  • Record Type: Publication
  • Report/Paper Numbers: 07-2640
  • Files: TRIS, TRB
  • Created Date: Feb 8 2007 7:20PM