Analysis of drowsy driving: exploring subpopulation risk with weighted contingency table tools

Patrick Coyle (), Chen Chen () and Nooreen Dabbish ()
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Patrick Coyle: Temple University
Chen Chen: Temple University
Nooreen Dabbish: Temple University

Computational Statistics, 2021, vol. 36, issue 3, No 4, 1605-1620

Abstract: Abstract The incidence of driving accidents due to human error, and drowsy driving in particular, is an important topic in the field of public health research, and might be considered preventable. Our study investigates the 606 police-reported drowsy driving accidents in 2013 as recorded in the NASS General Estimates System from the NHTSA. This study seeks to examine how the prevalence of drowsy driving in accidents differs between subpopulations and how this prevalence changes depending on the time of day. We explore these interactions using recent developments in survey-weighted ROC analysis. By doing so, we hope to offer employers and government agencies insight into what can be done to reduce the rate of injuries and fatalities related to drowsy driving.

Keywords: ROC; Complex survey design; Logistic regression; Data visualization; Drowsy driving (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s00180-021-01071-w

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