Reducing Treatment Selection Bias for Estimating Treatment Effects Using Propensity Score Method
Publication: Journal of Transportation Engineering
Volume 133, Issue 2
Abstract
Treatment selection bias leads to an inaccurate estimation of treatment effects as applied to specific sites or problem locations. Treatment selection bias is a major source of inconsistency in the results obtained from conventional before and after and cross-sectional models. One of the major expressions of treatment selection bias concerns the use of collision occurrence data in justifying intervention. For example, in highway safety field, a treatment is often introduced at a given site based on its high collision experience. Under normal conditions we would expect these collision numbers to return to a lower long term expected value, regardless of intervention. For treated sites, conventional observational models ascribe this reduction in collisions to the given treatment. This results in an overestimation of treatment effect. In this paper, a propensity score model is introduced that deals explicitly with treatment selection bias. The model is applied to Canadian highway–railway grade crossings data to estimate reductions in collision subject to upgrades in warning devices. The results of the propensity score model are compared for similar types of treatments to a number of before and after and cross-sectional models for both U.S. and Canadian data. The propensity score method is shown to reduce treatment selection bias and has probable merit that need to be further examined.
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Acknowledgments
This study was supported by the Transportation Development Centre of Transport Canada. The opinions, findings, and conclusions expressed in this paper are those of the writers and do not necessarily reflect the views of Transport Canada. The writers greatly appreciate the anonymous reviewers’ valuable comments.
References
Al-Masaeid, H. R. (1997). “Performance of safety evaluation methods.” J. Transp. Eng., 123(5), 364–369.
Bahar, G., Mollett, C., Persaud, B., Lyon, C., Smiley, A., Smahel, T., and McGee, H. (2004). “Safety evaluation of permanent raised pavement markers.” NCHRP Rep. No. 518, TRB, National Research Council, Washington, D.C.
Becker, S. O., and Ichino, A. (2002). “Estimation of average treatment effects based on propensity scores.” The Stata J., 2(4), 358–377.
Council, F., and Stewart, J. (1999). “Safety effects of conversion of rural two-lane to four-lane roadways based on cross-sectional models.” Transportation Research Record. 1665, Transportation Research Board, Washington, D.C., 35–43.
D’Agostino, R. B., Jr. (1998). “Tutorial in biostatistics: Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group.” Stat. Med., 17, 2265–2281.
Davis, G. A. (2000). “Accident reduction factors and causal inference in traffic safety studies: A review.” Accid. Anal Prev., 32, 95–109.
Davis, G. A. (2004). “Possible aggregation biases in road safety research and a mechanism approach to accident modeling.” Accid. Anal Prev., 36, 1119–1127.
Dehejia, R. H., and Wahba, S. W. (2002). “Propensity score-matching method for nonexperimental causal studies.” Rev. Econ. Stat., 84(1), 151–161.
Elvik, R. (2002). “The importance of confounding in observational before-and-after studies of road safety measures.” Accid. Anal Prev., 34, 631–635.
Elvik, R., Amundsen, F. H., and Hofset, F. (2001). “Road safety effects of bypasses.” Transportation Research Record. 1758, Transportation Research Board, Washington, D.C., 13–20.
Farr, E. H., and Hitz, J. S. (1985). “Effectiveness of motorist warning devices at rail-highway crossings.” Final Rep. No. FHWA/RD-85/015, Federal Highway Administration, Transportation Systems Center, Cambridge, Mass.
Federal Railroad Administration. (2002). GradeDec 2000 version 2.0 reference manual, Office of Policy and Program Development, Transportation System Center, U.S. Department of Transportation, Cambridge, Mass.
Gelman, A., and Meng, X.-L. (2004). Applied Bayesian modeling and casual inference from incomplete-data perspectives: An essential journey with Donald Rubin’s statistical family, Wiley, Chichester, U.K.
Harkey, D. (2005). Crash Reduction Factors for Traffic Engineering and Intelligent Transportation System Improvements: State-of-Knowledge Rep., NCHRP Research Result Digest 299, Interim Rep. No. NCHRP Project 17–25, National Cooperative Highway Research Program Project, Washington, D.C.
Harwood, D. W., Council, F. M., Hauer, F. M., Hughes, E. W., and Vogt, A. (2000). “Prediction of the expected safety performance of rural two-lane highways.” Rep. No. FHWA-RD-99-207, Federal Highway Administration, U.S. Department of Transportation, Washington, D.C.
Hauer, E. (1997). Observational before–after studies in road safety, Pergamon, U.K.
Hauer, E. (2005). “Cause and effect in observational cross-section studies on road safety.” 2nd Incomplete Draft, Proc., 84th Transportation Research Board Annual Meeting.
Hauer, E., and Persaud, B. N. (1987). “How to estimate the safety of rail-highway grade crossings and the safety effects of warning devices.” Transportation Research Record. 1114, Transportation Research Board, Washington, D.C., 131–140.
Lin, F., Sayed, T., and Deleur, P. (2003). “Estimating safety benefits of road improvements: case based approach.” J. Transp. Eng., 129(4), 385–391.
Lord, D., Washington, S. P., and Ivan, J. N. (2005). “Poisson, Poisson-gamma, and zero-inflated regression models of motor vehicle crashes: Balancing statistical fit and theory.” Accid. Anal Prev., 37(1), 35–46.
Lyon, C., Haq, A., Persaud, B. N., and Kodama, S. T. (2005). “Development of safety performance functions for signalized intersections in a large urban area and application to evaluation of left turn priority treatment.” Proc., 84th Annual Meeting of Transportation Research Board, Washington, D.C.
Pendleton, O. J. (1996). “Evaluation of accident analysis methodology.” Final Rep. No. FHWA-RD-96-039, Federal Highway Administration, Washington, D.C.
Persaud, B. N., Retting, R. A., Garder, P. E., and Lord, D. (2001). “Safety effect of roundabout conversions in the United States: Empirical Bayes observational before–after study.” Transportation Research Record. 1751, Transportation Research Board, Washington, D.C., 1–8.
Rosenbaum, P. R., and Rubin, D. B. (1983). “The central role of the propensity score in observational studies for casual effects.” Biometrika, 70, 41–55.
Rosenbaum, P. R., and Rubin, D. B. (1984). “Reducing bias in observational studies using subclassification on the propensity score.” J. Am. Stat. Assoc., 79, 516–524.
Rubin, D. B. (1997). “Estimating casual effects from large data sets using propensity scores.” Ann. Intern Med., 127(8), 757–763.
Saccomanno, F., Fu, L., Ren, C., and Miranda, L. (2003). “Identifying highway–railway grade crossing black spots: Phase 1.” Final Rep. No. TP 14168E, Transportation Development Centre, Transport Canada, Canada.
Saccomanno, F., and Lai, X. (2005). “Model for evaluating countermeasures at highway–railway grade crossings.” Transportation Research Record, Transportation Research Board, Washington, D.C.
Shankar, V., Milton, J., and Mannering, F. (1997). “Modeling accident frequencies as zero-altered probability processes: An empirical inquiry.” Accid. Anal Prev., 29, 829–837.
Transport Canada (TC). (2002). “RTD 10 road/railway grade crossings technical standards and inspection, testing and maintenance requirements.” Canada.
Tustin, B. H., Richards, H., McGee, H., and Patterson, R. (1986). Railroad–Railway Grade Crossing Handbook, 2nd Ed., Rep. FHWA-TS-86-215, Federal Highway Administration, U.S. Department of Transportation, Washington, D.C.
Yanovitzky, I., Zanutto, E., and Hornik, R. (2005). “Estimating casual effect of public health education campaigns using propensity score methodology.” Evaluation and Program Planning, 28, 209–220.
Zegger, C., and Council, F. (1995). “Safety effects associated with cross-sectional elements.” Transportation Research Record. 1512, Transportation Research Board, Washington, D.C., 29–36.
Information & Authors
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Published In
Journal of Transportation Engineering
Volume 133 • Issue 2 • February 2007
Pages: 112 - 118
Copyright
© 2007 ASCE.
History
Received: Nov 8, 2005
Accepted: Mar 20, 2006
Published online: Feb 1, 2007
Published in print: Feb 2007
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