Random Parameter Negative Binomial Model of Signalized Intersections

Factors affecting accident frequencies at 72 signalized intersections in the Gyeonggi-Do (province) over a four-year period (2007~2010) were explored using the random parameters negative binomial model. The empirical results from the comparison with fixed parameters binomial model show that the random parameters model outperforms its fixed parameters counterpart and provides a fuller understanding of the factors which determine accident frequencies at signalized intersections. In addition, elasticity and marginal effect were estimated to gain more insight into the effects of one-percent and one-unit changes in the dependent variable from changes in the independent variables.

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Traffic Accident Models using a Random Parameters Negative Binomial Model at Signalized Intersections: A Case of Daejeon Metropolitan Area

International Journal of Highway Engineering ◽

10.7855/ijhe.2018.20.2.119 ◽

2018 ◽

Vol 20 (2) ◽

pp. 119-126

Author(s):

Minho Park ◽

Jungyeol Hong

Keyword(s):

Metropolitan Area ◽

Traffic Accident ◽

Negative Binomial ◽

Signalized Intersections ◽

Negative Binomial Model ◽

Binomial Model ◽

Random Parameters

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Factors Affecting Under-Five Mortality in Ethiopia: A Multilevel Negative Binomial Model

Pediatric Health Medicine and Therapeutics ◽

10.2147/phmt.s290715 ◽

2020 ◽

Vol Volume 11 ◽

pp. 525-534

Author(s):

Bisrat Misganew Geremew ◽

Kassahun Alemu Gelaye ◽

Alemakef Wagnew Melesse ◽

Temesgen Yihunie Akalu ◽

Adhanom Gebreegziabher Baraki

Keyword(s):

Negative Binomial ◽

Negative Binomial Model ◽

Binomial Model ◽

Factors Affecting ◽

Under Five ◽

Multilevel Negative Binomial Model

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Predicting downgrade crash frequency with the random-parameters negative binomial model: Insights into the impacts of geometric variables on downgrade crashes in Wyoming

IATSS Research ◽

10.1016/j.iatssr.2019.09.002 ◽

2020 ◽

Vol 44 (2) ◽

pp. 94-102

Author(s):

Milhan Moomen ◽

Mahdi Rezapour ◽

Mustaffa Raja ◽

Khaled Ksaibati

Keyword(s):

Negative Binomial ◽

Negative Binomial Model ◽

Binomial Model ◽

Random Parameters ◽

Crash Frequency ◽

Geometric Variables

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Development of Accident Frequency Models with Random Parameters on Interstate Roadway Segments with and without Lighting Systems

Journal of Advanced Transportation ◽

10.1155/2017/4740532 ◽

2017 ◽

Vol 2017 ◽

pp. 1-8

Author(s):

Minho Park ◽

Dongmin Lee

Keyword(s):

Traffic Accidents ◽

Negative Binomial ◽

Unobserved Heterogeneity ◽

Random Parameter ◽

Random Parameters ◽

Factors Affecting ◽

Interstate Highways ◽

Estimated Parameters ◽

Fixed Parameter ◽

Lighting Systems

This study explored factors affecting traffic accidents in roadway segments with and without lighting systems using a random parameter negative binomial model. This study sought to make up for a shortcoming of the fixed parameter model that constrained the estimated parameters to be fixed across observations, by applying random parameters that can take into account unobserved heterogeneity. Three variables had a random parameter among nine significant variables in segments with lighting systems, while seven of the eleven significant variables in a segment without a lighting system had random parameters. The different influence of interstate highway geometrics on vehicle crashes with and without lighting systems found through this study considering unobserved heterogeneity may hopefully help reduce accident frequencies and consider installation of lighting systems on interstate highways in the future.

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Single-vehicle crashes along rural mountainous highways in Malaysia: An application of random parameters negative binomial model

Accident Analysis & Prevention ◽

10.1016/j.aap.2017.03.002 ◽

2017 ◽

Vol 102 ◽

pp. 153-164 ◽

Cited By ~ 22

Author(s):

Rusdi Rusli ◽

Md. Mazharul Haque ◽

Mark King ◽

Wong Shaw Voon

Keyword(s):

Negative Binomial ◽

Negative Binomial Model ◽

Binomial Model ◽

Vehicle Crashes ◽

Random Parameters ◽

Single Vehicle

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Modeling Hospitalization Decision and Utilization for the Elderly in China

Discrete Dynamics in Nature and Society ◽

10.1155/2021/4878442 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Xin Xu ◽

Dongxiao Chu

Keyword(s):

Negative Binomial ◽

Hospital Readmissions ◽

Poisson Model ◽

Medical Insurance ◽

The Elderly ◽

Negative Binomial Model ◽

Binomial Model ◽

Factors Affecting ◽

Basic Medical Insurance ◽

Basic Medical

Getting medical services has become more difficult and expensive in China, which led to a problem of illness not being treated and a large number of zeros in the statistics of being hospitalized for the elderly. Traditional classic models such as the Poisson model and the negative binomial model cannot fit this kind of data well. One aim of this study was to use zero-inflated and hurdle models to better solve the problem of excess zeros. Another aim was to discover the factors affecting the decision-making behavior of the elderly being hospitalized and hospitalization service utilization. Therefore, the XGBoost model was firstly introduced to rank the importance of influencing factors in this paper. It was found that the zero-inflated negative binomial model performed best. The results showed that the elderly who had enjoyed NRCM or ERBMI/URBMI were more likely to have a higher number of hospitalizations. This indicated that the high cost of hospitalization had prevented the willingness of the elderly being hospitalized, but the basic medical insurance had increased the times of their repeated hospital readmissions. Policy efforts should be made to improve the level of basic medical insurance.

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