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 socio-economic variables and ignoring measurement error, which can bias statistical inference. This paper presents Bayesian model analyse car crash occurrences at network-lattice level, taking into account error in spatial covariate. The suggested methodology is exemplified by collisions road network Leeds (UK) during 2011–2019. Traffic volumes are approximated using extensive counts obtained from mobile devices estimates adjusted correction.