Bayesian Hierarchical Poisson Regression Models: An Application to a Driving Study with Kinematic Events.

ABSTRACT: Although there is evidence that teenagers are at a high risk of crashes in the early months after licensure, the driving behavior of these teenagers is not well understood. The Naturalistic Teenage Driving Study (NTDS) is the first U.S. study to document continuous driving performance of newly-licensed teenagers during their first 18 months of licensure. Counts of kinematic events such as the number of rapid accelerations are available for each trip, and their incidence rates represent different aspects of driving behavior. We propose a hierarchical Poisson regression model incorporating over-dispersion, heterogeneity, and serial correlation as well as a semiparametric mean structure. Analysis of the NTDS data is carried out with a hierarchical Bayesian framework using reversible jump Mark

SUBMITTER: Kim S 

PROVIDER: S-EPMC3783969 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature