Conditional Quantile Analysis for Crash Count Data

Journal of Transportation Engineering

Volumn 137, Issue 9, 2011, Pages 601-607

  Qin, Xiao ^a   Reyes, Perla E ^b  

^a South Dakota State University   (United States)

^b University of California Santa Cruz   (United States)

Author keywords

Data heterogeneity; Intersection crashes.; Quantile regression

Indexed keywords

CONDITIONAL MEANS; CONDITIONAL QUANTILES; COVARIATES; CRASH DATA; DATA HETEROGENEITY; DESIRABLE METHODS; HEAVY-TAILS; HETEROGENEOUS DATA; HETEROSCEDASTICITY; INTERSECTION CRASHES.; MULTI-MODALITY; MULTI-YEAR PERIODS; NORMAL FORM; QR METHOD; QUANTILE REGRESSION; TRAFFIC VOLUMES; VARIABLE COEFFICIENTS;

HIGHWAY ACCIDENTS; HIGHWAY ENGINEERING;

DATA HANDLING;

ACCIDENT; ESTIMATION METHOD; HETEROGENEITY; QUANTITATIVE ANALYSIS; REGRESSION ANALYSIS;

EID: 80052677150     PISSN: 0733947X     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)TE.1943-5436.0000247     Document Type: Article

References (25)

1. Buchinsky M. Quantile regression with sample selection: Estimating women's return to education in the U. S. Empir. Econ. 2001, 26:87-113. 0377-7332, 10.1007/s001810000061
2. Chen C. An introduction to quantile regression and the QUANTREG procedure 2005, SAS Institute Inc., Gary, NC.
3. Chiou J.M. Muller H.G. Quasi-likelihood regression with unknown link and variance functions. J. Am. Stat. Assoc. 1998, 93:1376-1387. JSTNAL, 0162-1459, 10.2307/2670053
4. Fizenberger B. Hujur R. MaCurdy T.E. Schnabel R. Testing for uniform wage trends in West Germany: cohort analysis using quantile regression for censored data. Empir. Econ. 2001, 26:41-86. 0377-7332, 10.1007/s001810000048
5. Garcia J. Hernandez P.J. Lopez-Nicolas A. How wide is the gap? An investigation of gender wage differences using quantile regression. Empir. Econ. 2001, 26:149-167. 0377-7332, 10.1007/s001810000050
6. Geedipally S.R. Lord D. Effects of the varying dispersion parameter of Poisson-models on the estimation of confidence interval of crash prediction models. 2008, 46-54. Transportation Research Record 2061.
7. Gonzalez X. Miles D. Wage inequality in developing country: Decrease in minimum wage or increase in education returns. Empir. Econ. 2001, 26:135-148. 0377-7332, 10.1007/s001810000056
8. Hewson P. Quantile regression provides fuller analysis of speed data. Accid. Anal. Prev. 2008, 40:502-510. AAPVB5, 0001-4575, 10.1016/j.aap.2007.08.007
9. Knapp K.K. Campbell J. Kienert C. Intersection crash summary statistics for Wisconsin. 2005 Final Report, University of Wisconsin-Madison.
10. Koenker R. Bassett G. Regression quantiles. Econometrica 1978, 46:33-50. ECMTA7, 0098-1699, 10.2307/1913643
11. Koenker R. Hallock K.F. Quantile regression: An introduction. J. Econ. Perspect. 2001, 15:143-156.
12. Lord D. Washington S.P. Ivan J.N. Further notes on the application of zero inflated models in highway safety. Accid. Anal. Prev. 2007, 39(1):53-57. AAPVB5, 0001-4575, 10.1016/j.aap.2006.06.004
13. Machado J.A. F. Mata J. Earning functions in Portugal 1982-1994: Evidence from quantile regressions. Empir. Econ. 2001, 26:115-134. 0377-7332, 10.1007/s001810000049
14. Machado J.A. F. Santos Silva J.M. C. Quantiles for count. J. Am. Stat. Assoc. 2005, 100(472):1226-1237. JSTNAL, 0162-1459, 10.1198/016214505000000330
15. Miaou S.-P. Lord D. Modeling traffic crash-flow relationships for intersections: Dispersion parameter, functional form, and Bayes versus empirical Bayes methods. Transp. Res. Rec. 2003, 1840:31-40. TRREDM, 0361-1981, 10.3141/1840-04
16. Miranda-Moreno L.F. Fu F.F. Saccomanno L. Labbe A. Alternative risk models for ranking locations for safety improvement. Transp. Res. Rec. 2005, 1908:1-8. TRREDM, 0361-1981, 10.3141/1908-01
17. Mitra S. Washington S. On the nature of over-dispersion in motor vehicle crash prediction models. Accid. Anal. Prev. 2007, 39(3):459-468. AAPVB5, 0001-4575, 10.1016/j.aap.2006.08.002
18. Nelder J.A. Lee Y. Likelihood, quasi-likelihood and pseudo-likelihood: Some comparisons. J. R. Stat. Soc. Ser. 1992, 54(1):273-284. JSTBAJ, 0035-9246
19. Nielson H.S. Rosholm M. The public-private sector wage gap in Zambia in the 1990s: quantile regression approach. Empir. Econ. 2001, 26:169-182. 0377-7332, 10.1007/s001810000051
20. Palmer A. Losilla J.M. Vives J. Jimenez R. Overdispersion in the Poisson regression model. Methodology 2007, 3(3):89-99. 1614-1881, 10.1027/1614-2241.3.3.89
21. Park B.J. Lord D. Application of finite mixture models for vehicle crash data analysis. Accid. Anal. Prev. 2009, 41(4):683-691. AAPVB5, 0001-4575, 10.1016/j.aap.2009.03.007
22. Qin X. Ng M. Reyes P. Identifying crash-prone locations with quantile regress. Accid. Anal. Prev. 2010, 42(6):1531-1537. AAPVB5, 0001-4575, 10.1016/j.aap.2010.03.009
23. Taylor J. quantile regression approach to estimating the distribution of multiperiod returns. J. Derivatives 1999, 7:64-78. 1074-1240, 10.3905/jod.1999.319106
24. Wehby G.L. Murray J.C. Castilla E.E. Lopez-Camelo J.S. Ohsfeld R.L. Quantile effects of prenatal care utilization on birth weight in Argentina. Health Econ. 2009, 18(11):1307-1321. HEECEZ, 1099-1050, 10.1002/hec.1431
25. Winkelmann R. Reforming health care: Evidence from quantile regressions for counts. Health Econom. 2006, 25:131-145. HEECEZ, 1099-1050, 10.1016/j.jhealeco.2005.03.005