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Abstract
A growing concern on large-truck crashes increased over the years due to the potential economic
impacts and level of injury severity. This study aims to analyze the injury severities of multivehicle
large-trucks crashes on national highways. To capture and understand the complexities of
contributing factors, two random parameter discrete outcome models – random parameter ordered
probit and mixed logit – were estimated to predict the likelihood of five injury severity outcomes:
fatal, incapacitating, non-incapacitating, possible injury, and no-injury. Estimation findings
indicate that the level of injury severity is highly influenced by a number of complex interactions of
factors, namely, human, vehicular, road-environmental, and crash dynamics that can vary across
the observations.