Citation

Brijs T, Karlis D, Wets G. Proc. Road Saf. Four Continents Conf. 2007; 14: 12p.

Copyright

(Copyright © 2007, Conference Sponsor)

DOI

unavailable

PMID

unavailable

Abstract

In previous research, significant effects of weather conditions on car crashes have been found.However, most studies use monthly or yearly data and only few studies are available analyzing the impact of weather conditions on daily car crash counts. Furthermore, the studies that are available on a daily level do not model the data in a time-series context, hereby ignoring the temporal serial correlation that may be present in the data. In this paper, we introduce an Integer Autoregressive model for modeling count data with time interdependencies. The model is applied to daily car crash data and meteorological data from the Netherlands aiming at examining the risk impact of weather conditions on the observed counts. The results show that several assumptions related to the effect of weather conditions on crash counts are found to be significant in the data and that an appropriate statistical model should be used to account for the existing autocorrelation in the data.