Fan WD - Search Results

1

Mixed logit approach to analyzing pedestrian injury severity in pedestrian-vehicle crashes in North Carolina: Considering time-of-day and day-of-week.

Song L, Li Y, Fan WD, Liu P. Song L, et al. Among authors: fan wd. Traffic Inj Prev. 2021;22(7):524-529. doi: 10.1080/15389588.2021.1940983. Epub 2021 Jul 15. Traffic Inj Prev. 2021. PMID: 34264779

2

Modeling single-vehicle run-off-road crash severity in rural areas: Accounting for unobserved heterogeneity and age difference.

Gong L, Fan WD. Gong L, et al. Among authors: fan wd. Accid Anal Prev. 2017 Apr;101:124-134. doi: 10.1016/j.aap.2017.02.014. Epub 2017 Feb 20. Accid Anal Prev. 2017. PMID: 28226253

3

Modelling severity of pedestrian-injury in pedestrian-vehicle crashes with latent class clustering and partial proportional odds model: A case study of North Carolina.

Li Y, Fan WD. Li Y, et al. Among authors: fan wd. Accid Anal Prev. 2019 Oct;131:284-296. doi: 10.1016/j.aap.2019.07.008. Epub 2019 Jul 24. Accid Anal Prev. 2019. PMID: 31351231

4

Exploring injury severity in head-on crashes using latent class clustering analysis and mixed logit model: A case study of North Carolina.

Liu P, Fan W. Liu P, et al. Accid Anal Prev. 2020 Feb;135:105388. doi: 10.1016/j.aap.2019.105388. Epub 2019 Dec 5. Accid Anal Prev. 2020. PMID: 31812900

5

Modeling head-on crash severity with drivers under the influence of alcohol or drugs (DUI) and non-DUI.

Liu P, Fan WD. Liu P, et al. Among authors: fan wd. Traffic Inj Prev. 2020;21(1):7-12. doi: 10.1080/15389588.2019.1696964. Epub 2019 Dec 17. Traffic Inj Prev. 2020. PMID: 31846587

6

Combined latent class and partial proportional odds model approach to exploring the heterogeneities in truck-involved severities at cross and T-intersections.

Song L, Fan W. Song L, et al. Accid Anal Prev. 2020 Sep;144:105638. doi: 10.1016/j.aap.2020.105638. Epub 2020 Jun 26. Accid Anal Prev. 2020. PMID: 32599314

7

Exploring bicyclist injury severity in bicycle-vehicle crashes using latent class clustering analysis and partial proportional odds models.

Lin Z, Fan WD. Lin Z, et al. Among authors: fan wd. J Safety Res. 2021 Feb;76:101-117. doi: 10.1016/j.jsr.2020.11.012. Epub 2020 Dec 13. J Safety Res. 2021. PMID: 33653541

8

Exploring pedestrian injury severities at pedestrian-vehicle crash hotspots with an annual upward trend: A spatiotemporal analysis with latent class random parameter approach.

Song L, Fan WD, Li Y, Wu P. Song L, et al. Among authors: fan wd. J Safety Res. 2021 Feb;76:184-196. doi: 10.1016/j.jsr.2020.12.008. Epub 2020 Dec 29. J Safety Res. 2021. PMID: 33653550

9

Injury severity analysis of rollover crashes for passenger cars and light trucks considering temporal stability: A random parameters logit approach with heterogeneity in mean and variance.

Liu S, Fan WD, Li Y. Liu S, et al. Among authors: fan wd. J Safety Res. 2021 Sep;78:276-291. doi: 10.1016/j.jsr.2021.06.013. Epub 2021 Jul 6. J Safety Res. 2021. PMID: 34399924

10

Modeling pedestrian injury severity in pedestrian-vehicle crashes considering different land use patterns: Mixed logit approach.

Yang T, Fan WD, Song L. Yang T, et al. Among authors: fan wd. Traffic Inj Prev. 2023;24(2):114-120. doi: 10.1080/15389588.2022.2156789. Epub 2023 Jan 20. Traffic Inj Prev. 2023. PMID: 36662669

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