Incorporating temporal correlation into a multivariate random parameters Tobit model for modeling crash rate by injury severity

By Q. Zeng, Huiying Wen, Helai Huang, Xin Pei, Sze Chun Wong. 2018

70 citations recorded by the source corpus.

Subfields: Public Health, Environmental and Occupational Health, Pulmonary and Respiratory Medicine, Safety, Risk, Reliability and Quality

View Paper: https://www.semanticscholar.org/paper/53b605656356cad4f74fb950dd2ae0bbdf908e8e

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In Public Health, Environmental and Occupational Health

1. Xin Pei
2. Q. Zeng
3. Sze Chun Wong
4. Huiying Wen

In Safety, Risk, Reliability and Quality

1. Xin Pei
2. Q. Zeng
3. Sze Chun Wong
4. Huiying Wen

Citations in the corpus

• Jointly modeling area-level crash rates by severity: a Bayesian multivariate random-parameters spatio-temporal Tobit regression (2019, methodology): “The results show that KSI crash rates significantly decrease with increasing traffic volume, which is generally consistent with the findings in many previous studies on roadway segment-level crash rate analysis (Anastasopoulos et al. 2012; Zeng et al. 2017b, 2017a, 2018a).”