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    Revisiting crash spatial heterogeneity: A Bayesian spatially varying coefficients approach

    Xu, Pengpeng / Huang, Helai / Dong, Ni et al. | Elsevier | 2016
    Schlagwörter: Spatial heterogeneity , Unobserved heterogeneity

    Using vehicular trajectory data to explore risky factors and unobserved heterogeneity during lane-changing

    Chen, Qinghong / Gu, Ruifeng / Huang, Helai et al. | Elsevier | 2020
    Schlagwörter: Unobserved heterogeneity , Heterogeneity in means

    Assessing the explanatory and predictive performance of a random parameters count model with heterogeneity in means and variances

    Huo, Xiaoyan / Leng, Junqian / Hou, Qinzhong et al. | Elsevier | 2020
    Schlagwörter: Unobserved heterogeneity , Heterogeneity in means and variances

    The temporal stability of factors affecting driver injury severity in run-off-road crashes: A random parameters ordered probit model with heterogeneity in the means approach

    Yu, Miao / Zheng, Changjiang / Ma, Changxi et al. | Elsevier | 2020
    Schlagwörter: Heterogeneity in the means , Unobserved heterogeneity

    A random parameters with heterogeneity in means and Lindley approach to analyze crash data with excessive zeros: A case study of head-on heavy vehicle crashes in Queensland

    Behara, Krishna N.S. / Paz, Alexander / Arndt, Owen et al. | Elsevier | 2021
    Schlagwörter: Heterogeneity in means , Unobserved heterogeneity

    The dynamic tradeoff between safety and efficiency in discretionary lane-changing behavior: A random parameters logit approach with heterogeneity in means and variances

    Li, Ye / Gu, Ruifeng / Lee, Jaeyoung et al. | Elsevier | 2021
    Schlagwörter: Heterogeneity in means and variances , Unobserved heterogeneity

    Bivariate joint analysis of injury severity of drivers in truck-car crashes accommodating multilayer unobserved heterogeneity

    Song, Dongdong / Yang, Xiaobao / Yang, Yitao et al. | Elsevier | 2023
    Schlagwörter: Unobserved heterogeneity , Heterogeneity in the means

    Driver-injury severity in single-vehicle crashes in California: A mixed logit analysis of heterogeneity due to age and gender

    Kim, Joon-Ki / Ulfarsson, Gudmundur F. / Kim, Sungyop et al. | Elsevier | 2012
    Schlagwörter: Heterogeneity

    Macroscopic modeling of pedestrian and bicycle crashes: A cross-comparison of estimation methods

    Amoh-Gyimah, Richard / Saberi, Meead / Sarvi, Majid | Elsevier | 2016
    Schlagwörter: Unobserved heterogeneity

    Modeling spatiotemporal heterogeneity in interval-censored traffic incident time to normal flow by leveraging crowdsourced data: A geographically and temporally weighted proportional hazard analysis

    Gu, Yangsong / Zhang, Hairuilong / Han, Lee D. et al. | Elsevier | 2023
    Schlagwörter: Spatiotemporal heterogeneity

    The effect of zonal factors in estimating crash risks by transportation modes: Motor vehicle, bicycle and pedestrian

    Wang, Jie / Huang, Helai / Zeng, Qiang | Elsevier | 2016
    Schlagwörter: Unobserved heterogeneity

    Identifying crash-prone locations with quantile regression

    Qin, Xiao / Ng, Marie / Reyes, Perla E. | Elsevier | 2010
    Schlagwörter: Heterogeneity

    Investigating factors influencing rollover crash risk on mountainous interstates

    Alrejjal, Anas / Farid, Ahmed / Ksaibati, Khaled | Elsevier | 2021
    Schlagwörter: Unobserved heterogeneity effects

    Predicting effects of built environment on fatal pedestrian accidents at location-specific level: Application of XGBoost and SHAP

    Chang, Iljoon / Park, Hoontae / Hong, Eungi et al. | Elsevier | 2021
    Schlagwörter: Local heterogeneity

    An analysis of single-vehicle truck crashes on rural curved segments accounting for unobserved heterogeneity

    Islam, Mouyid / Hosseini, Parisa / Jalayer, Mohammad | Elsevier | 2021
    Schlagwörter: Unobserved heterogeneity , Mixed logit model with heterogeneity in means and variances

    Traffic accident segmentation by means of latent class clustering

    Depaire, Benoît / Wets, Geert / Vanhoof, Koen | Elsevier | 2008
    Schlagwörter: Heterogeneity

    Using latent class analysis and mixed logit model to explore risk factors on driver injury severity in single-vehicle crashes

    Li, Zhenning / Wu, Qiong / Ci, Yusheng et al. | Elsevier | 2019
    Schlagwörter: Unobserved heterogeneity

    Investigating the injury severity of single-vehicle truck crashes in a developing country

    Rahimi, Ehsan / Shamshiripour, Ali / Samimi, Amir et al. | Elsevier | 2020
    Schlagwörter: Heterogeneity

    A correlated random parameters tobit model to analyze the safety effects and temporal instability of factors affecting crash rates

    Hou, Qinzhong / Huo, Xiaoyan / Leng, Junqiang | Elsevier | 2019
    Schlagwörter: Unobserved heterogeneity

    Learning about injury severity from no-injury crashes: A random parameters with heterogeneity in means and variances approach

    Adanu, Emmanuel Kofi / Powell, Lawrence / Jones, Steven et al. | Elsevier | 2022
    Schlagwörter: Unobserved heterogeneity

    Identifying heterogeneous factors for driver injury severity variations in snow-related rural single-vehicle crashes

    Yu, Hao / Yuan, Runze / Li, Zhenning et al. | Elsevier | 2020
    Schlagwörter: Unobserved heterogeneity

    Severity analysis for large truck rollover crashes using a random parameter ordered logit model

    Azimi, Ghazaleh / Rahimi, Alireza / Asgari, Hamidreza et al. | Elsevier | 2019
    Schlagwörter: Heterogeneity

    Random parameter models of interstate crash frequencies by severity, number of vehicles involved, collision and location type

    Venkataraman, Narayan / Ulfarsson, Gudmundur F. / Shankar, Venky N. | Elsevier | 2013
    Schlagwörter: Heterogeneity

    Investigating pedestrian-vehicle crashes on interstate highways: Applying random parameter binary logit model with heterogeneity in means

    Hossain, Ahmed / Sun, Xiaoduan / Das, Subasish et al. | Elsevier | 2024
    Schlagwörter: Random parameter binary logit with heterogeneity in means (RPBL-HM) model , Unobserved heterogeneity

    Investigating factors affecting bus/minibus accident severity in a developing country for different subgroup datasets characterised by time, pavement, and light conditions

    Tamakloe, Reuben / Lim, Sungho / Sam, Enoch F. et al. | Elsevier | 2021
    Schlagwörter: Unobserved heterogeneity

    Does elderly safety matter? Associations between built environments and pedestrian crashes in Seoul, Korea

    Lee, Sugie / Yoon, Junho / Woo, Ayoung | Elsevier | 2020
    Schlagwörter: Economic heterogeneity

    Alternative approaches to modeling heterogeneity to analyze injury severity sustained by motorcyclists in two-vehicle crashes

    Wang, Huanhuan / Cui, Pengfei / Song, Dongdong et al. | Elsevier | 2023
    Schlagwörter: Scale heterogeneity , Heterogeneity in the means and variances

    Analyzing heterogeneous accident data from the perspective of accident occurrence

    Wong, Jinn-Tsai / Chung, Yi-Shih | Elsevier | 2007
    Schlagwörter: Heterogeneity

    Investigating the uniqueness of crash injury severity in freeway tunnels: A comparative study in Guizhou, China

    Zhou, Zichu / Meng, Fanyu / Song, Cancan et al. | Elsevier | 2021
    Schlagwörter: Unobserved heterogeneity

    Impact of heterogeneity of car-following behavior on rear-end crash risk

    Zhang, Junjie / Wang, Yunpeng / Lu, Guangquan | Elsevier | 2019
    Schlagwörter: Heterogeneity

    Towards activity-based exposure measures in spatial analysis of pedestrian–motor vehicle crashes

    Dong, Ni / Meng, Fanyu / Zhang, Jie et al. | Elsevier | 2020
    Schlagwörter: Spatial heterogeneity

    A full Bayesian multilevel approach for modeling interaction effects in single-vehicle crashes

    Cai, Zhenggan / Wei, Fulu / Guo, Yongqing | Elsevier | 2023
    Schlagwörter: Heterogeneity

    Geographically weighted machine learning for modeling spatial heterogeneity in traffic crash frequency and determinants in US

    Wang, Shuli / Gao, Kun / Zhang, Lanfang et al. | Elsevier | 2024
    Schlagwörter: Spatial heterogeneity

    Application of a model-based recursive partitioning algorithm to predict crash frequency

    Tang, Houjun / Donnell, Eric T. | Elsevier | 2019
    Schlagwörter: Heterogeneity

    A correlated random parameters approach to investigate large truck rollover crashes on mountainous interstates

    Alrejjal, Anas / Farid, Ahmed / Ksaibati, Khaled | Elsevier | 2021
    Schlagwörter: Unobserved heterogeneity effects

    Exploration of the police response time to motor-vehicle crashes in Pennsylvania, USA

    Liu, Chenhui | Elsevier | 2021
    Schlagwörter: Unobserved heterogeneity

    Deal or no deal: Can incentives encourage widespread adoption of intelligent speed adaptation devices?

    Chorlton, Kathryn / Hess, Stephane / Jamson, Samantha et al. | Elsevier | 2011
    Schlagwörter: Heterogeneity

    Investigating injury severities of motorcycle riders: A two-step method integrating latent class cluster analysis and random parameters logit model

    Chang, Fangrong / Xu, Pengpeng / Zhou, Hanchu et al. | Elsevier | 2019
    Schlagwörter: Unobserved heterogeneity

    Latent segmentation based count models: Analysis of bicycle safety in Montreal and Toronto

    Yasmin, Shamsunnahar / Eluru, Naveen | Elsevier | 2016
    Schlagwörter: Population heterogeneity

    A Hybrid Latent Class Analysis Modeling Approach to Analyze Urban Expressway Crash Risk

    Yu, Rongjie / Wang, Xuesong / Abdel-Aty, Mohamed | Elsevier | 2017
    Schlagwörter: Unobserved heterogeneity

    Modeling the effects of lake-effect snow related weather conditions on daily traffic crashes: A time series count data approach

    Ayon, Bandhan Dutta / Ofori-Amoah, Benjamin / Meng, Lei et al. | Elsevier | 2020
    Schlagwörter: Unobserved heterogeneity

    Factors associated with consecutive and non-consecutive crashes on freeways: A two-level logistic modeling approach

    Zichu, Zhou / Fanyu, Meng / Cancan, Song et al. | Elsevier | 2021
    Schlagwörter: Unobserved heterogeneity

    Bias properties of Bayesian statistics in finite mixture of negative binomial regression models in crash data analysis

    Park, Byung-Jung / Lord, Dominique / Hart, Jeffrey D. | Elsevier | 2009
    Schlagwörter: Heterogeneity

    Does time of day matter at highway work zone crashes?

    Al-Bdairi, Nabeel Saleem Saad | Elsevier | 2020
    Schlagwörter: Unobserved heterogeneity

    Spatial heterogeneity analysis of macro-level crashes using geographically weighted Poisson quantile regression

    Tang, Jinjun / Gao, Fan / Liu, Fang et al. | Elsevier | 2020
    Schlagwörter: Spatial heterogeneity

    Empirical comparison of the effects of urban and rural crashes on motorcyclist injury severities: A correlated random parameters ordered probit approach with heterogeneity in means

    Se, Chamroeun / Champahom, Thanapong / Jomnonkwao, Sajjakaj et al. | Elsevier | 2021
    Schlagwörter: Unobserved heterogeneity

    Correlated mixed logit modeling with heterogeneity in means for crash severity and surrogate measure with temporal instability

    Wang, Kai / Shirani-bidabadi, Niloufar / Razaur Rahman Shaon, Mohammad et al. | Elsevier | 2021
    Schlagwörter: Heterogeneity in means

    Do safety performance functions used for predicting crash frequency vary across space? Applying geographically weighted regressions to account for spatial heterogeneity

    Liu, Jun / Khattak, Asad J. / Wali, Behram | Elsevier | 2017
    Schlagwörter: Spatial heterogeneity

    Temporal instability assessment of injury severities of motor vehicle drivers at give-way controlled unsignalized intersections: A random parameters approach with heterogeneity in means and variances

    Zubaidi, Hamsa / Obaid, Ihsan / Alnedawi, Ali et al. | Elsevier | 2021
    Schlagwörter: Heterogeneity in mean and variance

    Investigating yielding behavior of heterogeneous vehicles at a semi-controlled crosswalk

    Wang, Yongjie / Su, Qian / Wang, Chao et al. | Elsevier | 2021
    Schlagwörter: Behavioral heterogeneity

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