ArticleJournal of safety research2019
Validation of not-at-fault driver representativeness assumption for quasi-induced exposure using U.S. national traffic databases.
Article in Journal of safety research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Variation in drivers' seat belt use by indicators of community-level vulnerability.Journal of safety research · 2023Article
- The difference in quasi-induced exposure to crashes involving various hazardous driving actions.PloS one · 2023Article
- Sex Differences in the Amount and Patterns of Car-Driving Exposure in Spain, 2014 to 2017: An Application of a Quasi-Induced Exposure Approach.International journal of environmental research and public health · 2021Article
- Older Driver Crash Involvement and Fatalities, by Age and Sex, 2000-2017.Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2021Article
- Driver Liability Assessment in Vehicle Collisions in Spain.International journal of environmental research and public health · 2021Article
- Validating the representativeness assumption of the quasi-induced exposure method using a national representative field observation survey.Traffic injury prevention · 2021Article
- Explaining the Association between Driver's Age and the Risk of Causing a Road Crash through Mediation Analysis.International journal of environmental research and public health · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
introductionThe 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.
methodUsing 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.
resultsThe 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.
conclusionsOverall, 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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