Filtering out confounding effects, such as regression to the mean (RTM) and trend, is crucial when using road safety data to make decisions. For example, ignoring such effects can exaggerate estimates of treatment effects in road safety scheme before-and-after studies; similarly, such effects should be properly handled when attempting to make predictions of road safety hotspots in future time periods.

The Newcastle University Statistics of Road Safety Group (NUSRG) has developed a software tool to enable road safety practitioners to make better data-informed decisions. The tool’s main dashboard supports simple data visualisation, as well as the fitting of statistical models that enable the implementation of cutting-edge methods for handling confounders such as RTM and trend.

In this presentation we will demonstrate the tool, describe the underpinning methods and give summaries of past and ongoing collaborations with road safety practitioners across the UK, including road safety partnerships in Cumbria, North Yorkshire and Gateshead; and internationally with organisations in Lisbon and New York, as well as commercially with PTV Group in Germany and LOGIT in Portugal. The aim of this presentation is to raise awareness of this work among practitioners in the hope of starting new collaborations with organisations that can use these methods to support their road safety decision making.

Lee Fawcett and Joe Matthews, Newcastle University

Biogs to follow