Measurement Error Models for Spatial Network Lattice Data: Analysis of Car Crashes in Leeds

Abstract: Road casualties represent an alarming concern for modern societies. During the last years, several authors proposed sophisticated approaches to help authorities implement new policies. These models were usually developed considering a set of socioeconomic variables and ignoring the measurement error, which can bias the statistical inference. This paper presents a Bayesian model to analyse car crashes occurrences at the network-lattice level, taking into account measurement error in the spatial covariate. The suggested methodology is exemplified by considering the collisions in the road network of Leeds (UK) during 2011-2019. Traffic volumes are approximated using an extensive set of counts obtained from mobile devices and the estimates are adjusted using a spatial measurement error correction.