TY - JOUR
T1 - The odds of accident-type casualties in a Peruvian jungle road
AU - Huaman Meza, Angela Denisse
AU - Soto, Gian Carlos Meza
AU - Guillen, Jahir Chuquillanqui
AU - Campomanes, Giovene Perez
N1 - Publisher Copyright:
© 2023 by the authors; licensee Growing Science, Canada.
PY - 2023/3/1
Y1 - 2023/3/1
N2 - The current analysis analyzed the odds of casualties by road accidents. Hence, data were classified into tertiles for better research, and accident types were classified into five following the authority methodology: rollovers, crash, roadway departure, special accident, and car capsizing. Multi-logistic regression was employed for the data analysis. This research found that rollover was the most deadly accident, and the crash was the most probable to cause injuries.
AB - The current analysis analyzed the odds of casualties by road accidents. Hence, data were classified into tertiles for better research, and accident types were classified into five following the authority methodology: rollovers, crash, roadway departure, special accident, and car capsizing. Multi-logistic regression was employed for the data analysis. This research found that rollover was the most deadly accident, and the crash was the most probable to cause injuries.
KW - Casualties
KW - Multiple logistic regression
KW - Road accidents
KW - Road safety
UR - http://www.scopus.com/inward/record.url?scp=85152286857&partnerID=8YFLogxK
U2 - 10.5267/j.dsl.2023.3.003
DO - 10.5267/j.dsl.2023.3.003
M3 - Original Article
AN - SCOPUS:85152286857
SN - 1929-5804
VL - 12
SP - 163
EP - 168
JO - Decision Science Letters
JF - Decision Science Letters
IS - 2
ER -