Validation of not-at-fault driver representativeness assumption for quasi-induced exposure using U.S. national traffic databases |
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| Institution: | 1. The Center for Injury Research and Policy, Abigail Wexner Research Institute at Nationwide Children’s Hospital, Columbus, OH, United States;2. Department of Pediatrics, College of Medicine, The Ohio State University, Columbus, United States;3. Graduate Center for Gerontology, College of Public Health, University of Kentucky, Lexington, KY, United States;4. Department of Civil Engineering, College of Engineering, University of Kentucky, Lexington, KY, United States;5. Division of Epidemiology, College of Public Health, The Ohio State University, Columbus, OH, United States;1. Center for Injury Research and Prevention;2. Department of Pediatrics, Division of Emergency Medicine, the Children’s Hospital of Philadelphia;3. Center for Clinical Epidemiology and Biostatistics;4. Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania;5. Department of Biostatistics, School of Public Health;6. Survey Methodology Program, Institute for Social Research, University of Michigan, Ann Arbor, Michigan;1. Center for Injury Research and Prevention, The Children’s Hospital of Philadelphia, 3535 Market Street, Suite 1150, Philadelphia, PA 19104, USA;2. Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine at the University of Pennsylvania, 423 Guardian Drive, Philadelphia, PA 19104, USA;3. The Department of Pediatrics, Division of Emergency Medicine, The Children’s Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, 3401 Civic Center Blvd., Philadelphia, PA 19104, USA;4. Department of Biostatistics, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109, USA;5. Survey Methodology Program, Institute for Social Research, University of Michigan, Rm. 4068, 426 Thompson Street, Ann Arbor, MI 48109, USA;1. Department of Civil and Environmental Engineering, California Polytechnic State University, 1 Grand Ave, San Luis Obispo, CA 93407;2. Wyoming Technology Transfer Center, Department of Civil & Architectural Engineering, University of Wyoming, 1000 E. University Avenue, Dept. 3295, Laramie, WY 82071, United States;1. University of Iowa Injury Prevention Research Center, 2195 Westlawn, Iowa City, IA 52242, USA;2. Department of Epidemiology, College of Public Health, University of Iowa, 145 North Riverside Drive, Iowa City, IA 52242, USA;3. Department of Biostatistics, College of Public Health, University of Iowa, 145 North Riverside Drive, Iowa City, IA 52242, USA;4. Department of Occupational and Environmental Health, College of Public Health, University of Iowa, 145 North Riverside Drive, Iowa City, IA 52242, USA |
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| Abstract: | Introduction:The quasi-induced exposure (QIE) method has been widely implemented into traffic safety research. One of the key assumptions of QIE method is that not-at-fault drivers represent the driving population at the time of a crash. Recent studies have validated the QIE representative assumption using not-at-fault drivers from three-or-more vehicle crashes (excluding the first not-at-fault drivers; D3_other) as the reference group in single state crash databases. However, it is unclear if the QIE representativeness assumption is valid on a national scale and is a representative sample of driving population in the United States. The aims of this study were to assess the QIE representativeness assumption on a national scale and to evaluate if D3_other could serve as a representative sample of the U.S. driving population. Method: Using the Fatality Analysis Reporting System (FARS) and the National Occupant Protection Use Survey (NOPUS), distributions of driver gender, age, vehicle type, time, and roadway type among the not-at-fault drivers in clean two-vehicle crashes, the first not-at-fault drivers in three-or-more-vehicle crashes, and the remaining not-at-fault drivers in three-or-more vehicle crashes were compared to the driver population observed in NOPUS. Results: The results showed that with respect to driver gender, vehicle type, time, and roadway type, drivers among D3_other did not show statistical significant difference from NOPUS observations. The age distribution of D3_other driver was not practically different to NOPUS observations. Conclusions: Overall, we conclude that D3_other drivers in FARS represents the driving population at the time of the crash. Practical applications: Our study provides a solid foundation for future studies to utilize D3_other as the reference group to validate the QIE representativeness assumption and has potential to increase the generalizability of future FARS studies. |
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| Keywords: | Clean multiple vehicle crashes Quasi-induced exposure Representativeness assumption Fatality Analysis Reporting System |
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