GoToWebinar: This webinar, organised by CIHT East Midlands, will look at the characteristics associated with developing safety models from the perspective of statistical performance and logic.
In this presentation, Dr Dominique will discuss the characteristics associated with developing safety models from the perspective of statistical performance and logic.
In highway safety, researchers usually develop or apply new and innovative models or methods and select the best model because it fits the data better. In most cases, the new proposed model adds a level of complexity that may not be warranted and further muddies the water to explain how factors influence safety and crash risk.
Dr Dominique will cover important limitation and pitfalls and offer approaches to avoid them.
The presentation will be followed by a Q&A session.
This webinar is open to both CIHT Members and non-members. It may be of particular interest to academics, undergraduate and graduate students in highway safety and civil engineering as well as those working within these fields.
Dr Dominique Lord, Professor of Civil Engineering at Texas A&M University
Dr. Dominique Lord is a Professor and A.P. and Florence Wiley Faculty Fellow in the Zachry Department of Civil and Environmental Engineering at Texas A&M University. Over the last 25 years, Dr. Lord has conducted numerous research studies in the United States, Canada, and across the world. The results of his research have been used by researchers across the world and several areas, including medicine, accounting, mathematics and statistics, biology and most engineering disciplines among others.
Dr. Lord’s primary interests are conducting fundamental research on crash analysis methodology, new and innovative statistical methods for modeling motor vehicle collisions, and before-after evaluation techniques. He has had more than 150 papers published in peer-reviewed journals; co-authored the textbook titled “Highway Safety Analytics and Modeling;” and presented more than 135 papers at international conferences with a peer-reviewed process.
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