Statistical and Econometric Methods for Transportation Data Analysis

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Praise for the Second Edition:

The second edition introduces an especially broad set of statistical methods ... As a lecturer in both transportation and marketing research, I find this book an excellent textbook for advanced undergraduate, Master's and Ph.D. students, covering topics from simple descriptive statistics to complex Bayesian models. ... It is one of the few books that cover an extensive set of statistical methods needed for data analysis in transportation. The book offers a wealth of examples from the transportation field. -The American Statistician

Statistical and Econometric Methods for Transportation Data Analysis, Third Edition offers an expansion over the first and second editions in response to the recent methodological advancements in the fields of econometrics and statistics and to provide an increasing range of examples and corresponding data sets. It describes and illustrates some of the statistical and econometric tools commonly used in transportation data analysis. It provides a wide breadth of examples and case studies, covering applications in various aspects of transportation planning, engineering, safety, and economics. Ample analytical rigor is provided in each chapter so that fundamental concepts and principles are clear and numerous references are provided for those seeking additional technical details and applications.

 

New to the Third Edition

 

Updated references and improved examples throughout.

 

 

New sections on random parameters linear regression and ordered probability models including the hierarchical ordered probit model.

 

 

A new section on random parameters models with heterogeneity in the means and variances of parameter estimates.

 

 

Multiple new sections on correlated random parameters and correlated grouped random parameters in probit, logit and hazard-based models.

 

 

A new section discussing the practical aspects of random parameters model estimation.

 

 

A new chapter on Latent Class Models.

 

 

A new chapter on Bivariate and Multivariate Dependent Variable Models.

 

Statistical and Econometric Methods for Transportation Data Analysis, Third Edition can serve as a textbook for advanced undergraduate, Masters, and Ph.D. students in transportation-related disciplines including engineering, economics, urban and regional planning, and sociology. The book also serves as a technical reference for researchers and practitioners wishing to examine and understand a broad range of statistical and econometric tools required to study transportation problems.

Author Biography: Simon Washington is Professor of Civil Engineering at the University of Queensland. He is recognized internationally for his contributions in the fields of behavioral econometrics applied in the areas of transport and urban planning, transport safety and risk across all travel modes, and travel behavior. He is Associate Editor or Editorial Advisory Board Member on six leading international transport journals (Korean Journal of Transportation Engineering; Analytic Methods in Accident Research; Accident Analysis and Prevention; Journal of Transport and Health; Transportation Research Part A; and Journal of Sustainable Transportation). He has authored or co-authored more than 100 peer-reviewed journal articles and a second edition of a textbook adopted in over 20 countries, and 6 book chapters. He has been lead investigator on more than $26 million on externally supported research and has secured nationally competitive research grants in Australia including the Australian Research Council, the National Health and Medical Research Council, and the Cooperative Research Center, and in the United States from the National Academy of Sciences, the National Highway Traffic and Safety Administration, and the Federal Highway Administration. Prior to joining the University of Queensland he served on the faculties of the Queensland University of Technology, University of California Berkeley, Arizona State University, the University of Arizona, and the Georgia Institute of Technology. He has been visiting professor at Ajou University (South Korea), University of Sydney, and Loughborough University (UK). Professor Matthew Karlaftis passed away unexpectedly in June 2014. He did extensive work in the areas of urban transportation, transportation planning and operations, and emergency response. He was a coauthor of an international bestselling book on transportation econometrics and statistics, two textbooks on transportation planning and public transportation, many book chapters, more than 100 publications in peer-reviewed journals, and many publications in conference proceedings, all highly cited worldwide. He participated in more than 45 national and European research projects as the principal or co-principal investigator. He was deeply involved in editorial activities. He served as the editor in chief for Transportation Research Part C, European editor of ASCE's Journal of Transportation Engineering, associate editor of ASCE's Journal of Infrastructure Systems, and an editorial board member for eight other journals. He was the recipient of the Fulbright Scholar Grant (2006-2007), the ASCE Walter L. Huber Civil Engineering Research Prize (2005), the TRB ABJ80 Committee on Statistical Methods Best Paper Award (2009), and the ASCE State-of-the-Art Paper Award (2011). He served on many technical committees and was a member of a variety of professional organizations and honor societies in Greece and the United States. He had a long association with the Hellenic Institute of Transportation Engineers where he served as vice president (2010-2012) and president (2012-2014). Fred Mannering is Professor of Civil and Environ mental Engineering (with a courtesy appointment in Economics) at the University of South Florida. He received his undergraduate degree from the University of Saskatchewan, masters from Purdue University, and doctorate from the Massachusetts Institute of Technology. Prior to joining the University of South Florida, he was an Assistant Professor at the Pennsylvania State University, Professor and Department Chair at the University of Washington, and School Head and Charles Pankow Professor at Purdue University. His research interests are in the application of econometric and statistical methods to the analysis of highway safety, transportation economics, vehicle demand, travel behavior and a variety of other engineering-related problems. He has published extensively with over 140 journal articles and two books: Principles of Highway Engineering and Traffic Analysis and Statistical and Econometric Methods for Transportation Data Analysis. He has received numerous awards and recognitions including ASCE's Wilbur S. Smith Award (2005), James Laurie Prize (2009), and Arthur M. Wellington Prize (2009). He has been acknowledged as a Web-of-Science Highly Cited Researcher (2019). Dr. Mannering is currently Editor-in-Chief (and founding Editor) of the Elsevier Science journal Analytic Methods in Accident Research and previous Editor-in-Chief (2003-2012) and current Distinguished Editorial Board Member of the Elsevier Science journal Transportation Research Part B: Methodological. He also serves on the editorial boards of Accident Analysis and Prevention and Transportation Research Part C: Emerging Technologies. Panagiotis Anastasopoulos is Associate Professor and Stephen E. Still Chair of Transportation Engineering, in the Department of Civil, Structural and Environmental Engineering at the University at Buffalo, The State University of New York. He is also the Director of the Stephen Still Institute for Sustainable Transportation and Logistics at University at Buffalo. He received his bachelor's degree from the Athens University of Economics and Business, and his master's and doctorate from Purdue University. His research interests include statistical and econometric modeling of engineering problems, transportation safety, planning for flying cars, urban air mobility, infrastructure systems, crisis management, transportation economics, and travel behavior. In these areas, he has published over 100 papers, books/book chapters, and reports. He is Associate Editor (and founding Editorial Board Member) of Elsevier Science's journal Analytic Methods in Accident Research, Associate Editor of the ASCE Journal of Infrastructure Systems and of the journal Frontiers in Built Environment, Transportation and Transit Systems (Nature Publishing Group), Advisory Editor of the International Journal of Critical Illness and Injury Science, and Editorial Board Member of Elsevier Science's journal Accident Analysis and Prevention. He is also the Chair of the Transportation Research Board ABJ80 Statistical Methods Committee, and Vice Chair of the ASCE T&DI Transportation Economics and Finance Committee. He has been acknowledged as a Web-of-Science Highly Cited Researcher (2019), has received the Outstanding Reviewer award for the ASCE Journals of Infrastructure Systems and Transportation Engineering, and his project on improvements of safety at high-speed rural intersections was selected as a high value research project by the American Association of State Highway and Transportation Officials (AASHTO).

Preface
Part I Fundamentals
1. Statistical Inference I: Descriptive Statistics
2. Statistical Inference II: Interval Estimation, Hypothesis Testing
and Population Comparisons
Part II Continuous Dependent Variable Models
3. Linear Regression
4. Violations of Regression Assumptions
5. Simultaneous-Equation Models
Appendix 5A
A Note on GLS Estimation.
7. Background and Exploration in Time Series
8. Forecasting in Time Series: Autoregressive Integrated Moving Average (ARIMA) Models and Extensions
9. Latent Variable Models
10. Duration Models

Part III Count and Discrete Dependent Variable Models
11. Count Data Models
12. Logistic Regression
13. Discrete Outcome Models
14. Ordered Probability Models
15. Discrete/Continuous Models
Part IV Other Statistical Methods
16. Random-Parameter Models
17. Latent Class (Finite Mixture) Models
18. Bivariate and Multivariate Dependent Variable Models
19. Bayesian Models
Appendix A Statistical Fundamentals
Appendix B Statistical Tables
Appendix C Variable Transformations
References