A new spatial and flexible multivariate random-coefficients model for the analysis of pedestrian injury counts by severity level

Publication date: December 2017 Source:Analytic Methods in Accident Research, Volume 16 Author(s): Chandra R. Bhat, Sebastian Astroza, Patrícia S. Lavieri We propose in this paper a spatial random coefficients flexible multivariate count model to examine, at the spatial level of a census tract, the number of pedestrian injuries by injury severity level. Our model, unlike many other macro-level pedestrian injury studies in the literature, explicitly acknowledges that risk factors for different types of pedestrian injuries can be very different, as well as accounts for unobserved heterogeneity in the risk factor effects. We also recognize the multivariate nature of the injury counts by injury severity level within each census tract (as opposed to independently modeling the count of pedestrian injuries by severity level). In concrete methodological terms, our model: (a) allows a full covariance matrix for the random coefficients (constant heterogeneity, or CH, and slope heterogeneity, or SH, effects) characterizing spatial heterogeneity for each count category, (b) addresses excess zeros (or any other excess count value for that matter) within a multivariate count setting in a simple and elegant fashion, while recognizing multivariateness engendered through covariances in both the CH and SH effects, (c) accommodates spatial dependency through a spatial autoregressive lag structure, allowing for varying spatial autoregressive parameters across count categories, and (d) capt...
Source: Analytic Methods in Accident Research - Category: Accident Prevention Source Type: research