Methodology Application: Logistic Regression the Using CODES Data
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Methodology Application: Logistic Regression the Using CODES Data

Filetype[PDF-775.02 KB]


  • English
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    Details:

    • Creators:
      Walker, Jonathan
    • Corporate Contributors:
      National Center for Statistics and Analysis (U.S.)
    • Subject/TRT Terms:
    • Publication/ Report Number:
      HS-808 460
    • DOI:
    • Resource Type:
      Research Paper
    • TRIS Online Accession Number:
      00736060
    • NTL Classification:
      NTL-SAFETY AND SECURITY-Accidents;NTL-REFERENCES AND DIRECTORIES-REFERENCES AND DIRECTORIES;NTL-REFERENCES AND DIRECTORIES-Statistics;
    • Abstract:
      Congress directed the Secretary of Transportation, through the Intermodal

      Surface Transportation Efficiency Act (ISTEA) of 1991, to carry out a study or

      studies to determine the impact of safety belt and motorcycle helmet use. In

      order to carry out the studies described in the Act, the National Highway

      Traffic Safety Administration (NHTSA) used the resources provided in the

      legislation to fund states to develop Crash Outcome Data Evaluation Systems

      (CODES). The states in the CODES project used a cost-efficient method

      (probabilistic linkage) of matching crash data to medical and insurance data.

      NHTSA wants to expand the establishment and use of these linked data sets.

      This report addresses logistic regression, a powerful statistical analysis, as

      a tool to use with the material in the CODES database. It allows researchers

      using qualitative measures of effectiveness, such as 'died versus survived,' to

      investigate relationships between that measure and many other measures

      simultaneously, whether those other measures are qualitative or quantitative.

      This document will introduce logistic regression to analysts who have limited

      experience or no experience with it. This paper is intended for users who have

      had course work in applied statistics at the college level or higher and who

      are familiar with the Chi-square test and linear regression. 39p. First issued

      April 30, 1996; Revised September 6, 1996.

    • Format:
      PDF
    • Funding:
      OPM 91-2973
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