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HEALTH AND SAFETY (532 journals)                  1 2 3 | Last

Showing 1 - 200 of 203 Journals sorted alphabetically
16 de Abril     Open Access  
A Life in the Day     Hybrid Journal   (Followers: 10)
Acta Informatica Medica     Open Access   (Followers: 1)
Acta Scientiarum. Health Sciences     Open Access  
Adultspan Journal     Hybrid Journal  
Advances in Child Development and Behavior     Full-text available via subscription   (Followers: 10)
Advances in Public Health     Open Access   (Followers: 23)
African Health Sciences     Open Access   (Followers: 2)
African Journal for Physical, Health Education, Recreation and Dance     Full-text available via subscription   (Followers: 6)
African Journal of Health Professions Education     Open Access   (Followers: 6)
Afrimedic Journal     Open Access   (Followers: 2)
Air Quality, Atmosphere & Health     Hybrid Journal   (Followers: 3)
AJOB Primary Research     Partially Free   (Followers: 3)
American Journal of Family Therapy     Hybrid Journal   (Followers: 11)
American Journal of Health Economics     Full-text available via subscription   (Followers: 13)
American Journal of Health Education     Hybrid Journal   (Followers: 31)
American Journal of Health Promotion     Hybrid Journal   (Followers: 24)
American Journal of Health Sciences     Open Access   (Followers: 6)
American Journal of Health Studies     Full-text available via subscription   (Followers: 11)
American Journal of Preventive Medicine     Hybrid Journal   (Followers: 26)
American Journal of Public Health     Full-text available via subscription   (Followers: 240)
American Journal of Public Health Research     Open Access   (Followers: 29)
American Medical Writers Association Journal     Full-text available via subscription   (Followers: 2)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 4)
Annals of Global Health     Open Access   (Followers: 9)
Annals of Health Law     Open Access   (Followers: 3)
Annals of Tropical Medicine and Public Health     Open Access   (Followers: 15)
Applied Biosafety     Hybrid Journal  
Applied Research In Health And Social Sciences : Interface And Interaction     Open Access   (Followers: 2)
Archive of Community Health     Open Access  
Archives of Medicine and Health Sciences     Open Access   (Followers: 3)
Arquivos de Ciências da Saúde     Open Access  
Asia Pacific Journal of Counselling and Psychotherapy     Hybrid Journal   (Followers: 8)
Asia Pacific Journal of Health Management     Full-text available via subscription   (Followers: 3)
Asia-Pacific Journal of Public Health     Hybrid Journal   (Followers: 8)
Asian Journal of Gambling Issues and Public Health     Open Access   (Followers: 3)
Association of Schools of Allied Health Professions     Full-text available via subscription   (Followers: 6)
Atención Primaria     Open Access   (Followers: 1)
Australasian Journal of Paramedicine     Open Access   (Followers: 3)
Australian Advanced Aesthetics     Full-text available via subscription   (Followers: 4)
Australian Family Physician     Full-text available via subscription   (Followers: 3)
Australian Indigenous HealthBulletin     Free   (Followers: 6)
Autism & Developmental Language Impairments     Open Access   (Followers: 6)
Behavioral Healthcare     Full-text available via subscription   (Followers: 6)
Best Practices in Mental Health     Full-text available via subscription   (Followers: 8)
Bijzijn     Hybrid Journal   (Followers: 2)
Bijzijn XL     Hybrid Journal   (Followers: 1)
Biomedical Safety & Standards     Full-text available via subscription   (Followers: 8)
BLDE University Journal of Health Sciences     Open Access  
BMC Oral Health     Open Access   (Followers: 5)
BMC Pregnancy and Childbirth     Open Access   (Followers: 20)
BMJ Simulation & Technology Enhanced Learning     Full-text available via subscription   (Followers: 8)
Brazilian Journal of Medicine and Human Health     Open Access  
Buletin Penelitian Kesehatan     Open Access   (Followers: 2)
Buletin Penelitian Sistem Kesehatan     Open Access  
Bulletin of the World Health Organization     Open Access   (Followers: 17)
Cadernos de Educação, Saúde e Fisioterapia     Open Access   (Followers: 1)
Cadernos Saúde Coletiva     Open Access   (Followers: 1)
Canadian Family Physician     Partially Free   (Followers: 12)
Canadian Journal of Community Mental Health     Full-text available via subscription   (Followers: 12)
Canadian Journal of Human Sexuality     Hybrid Journal   (Followers: 1)
Canadian Journal of Public Health     Full-text available via subscription   (Followers: 20)
Case Reports in Women's Health     Open Access   (Followers: 3)
Case Studies in Fire Safety     Open Access   (Followers: 13)
Central Asian Journal of Global Health     Open Access   (Followers: 2)
Central European Journal of Public Health     Full-text available via subscription   (Followers: 4)
CES Medicina     Open Access  
Child Abuse Research in South Africa     Full-text available via subscription   (Followers: 1)
Child's Nervous System     Hybrid Journal  
Childhood Obesity and Nutrition     Open Access   (Followers: 10)
Children     Open Access   (Followers: 2)
CHRISMED Journal of Health and Research     Open Access  
Christian Journal for Global Health     Open Access  
Ciência & Saúde Coletiva     Open Access   (Followers: 2)
Ciencia y Cuidado     Open Access   (Followers: 1)
Ciencia, Tecnología y Salud     Open Access  
ClinicoEconomics and Outcomes Research     Open Access   (Followers: 2)
CME     Hybrid Journal   (Followers: 1)
CoDAS     Open Access  
Community Health     Open Access   (Followers: 2)
Conflict and Health     Open Access   (Followers: 8)
Contraception and Reproductive Medicine     Open Access  
Curare     Open Access  
Current Opinion in Behavioral Sciences     Hybrid Journal   (Followers: 3)
Day Surgery Australia     Full-text available via subscription   (Followers: 2)
Digital Health     Open Access   (Followers: 3)
Dramatherapy     Hybrid Journal   (Followers: 2)
Drogues, santé et société     Full-text available via subscription  
Duazary     Open Access   (Followers: 1)
Early Childhood Research Quarterly     Hybrid Journal   (Followers: 16)
East African Journal of Public Health     Full-text available via subscription   (Followers: 3)
Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity     Hybrid Journal   (Followers: 18)
EcoHealth     Hybrid Journal   (Followers: 4)
Education for Health     Open Access   (Followers: 5)
electronic Journal of Health Informatics     Open Access   (Followers: 6)
ElectronicHealthcare     Full-text available via subscription   (Followers: 4)
Elsevier Ergonomics Book Series     Full-text available via subscription   (Followers: 5)
Emergency Services SA     Full-text available via subscription   (Followers: 2)
Ensaios e Ciência: Ciências Biológicas, Agrárias e da Saúde     Open Access  
Environmental Disease     Open Access   (Followers: 2)
Environmental Sciences Europe     Open Access   (Followers: 2)
Epidemics     Open Access   (Followers: 4)
Epidemiologic Perspectives & Innovations     Open Access   (Followers: 5)
Epidemiology, Biostatistics and Public Health     Open Access   (Followers: 19)
Ethics, Medicine and Public Health     Full-text available via subscription   (Followers: 3)
Ethiopian Journal of Health Development     Open Access   (Followers: 8)
Ethiopian Journal of Health Sciences     Open Access   (Followers: 7)
Ethnicity & Health     Hybrid Journal   (Followers: 13)
European Journal of Investigation in Health, Psychology and Education     Open Access   (Followers: 2)
European Medical, Health and Pharmaceutical Journal     Open Access  
Evaluation & the Health Professions     Hybrid Journal   (Followers: 10)
Evidence-based Medicine & Public Health     Open Access   (Followers: 6)
Evidência - Ciência e Biotecnologia - Interdisciplinar     Open Access  
Expressa Extensão     Open Access  
Face à face     Open Access   (Followers: 1)
Families, Systems, & Health     Full-text available via subscription   (Followers: 8)
Family & Community Health     Partially Free   (Followers: 12)
Family Medicine and Community Health     Open Access   (Followers: 6)
Family Relations     Partially Free   (Followers: 11)
Fatigue : Biomedicine, Health & Behavior     Hybrid Journal   (Followers: 2)
Food and Public Health     Open Access   (Followers: 11)
Frontiers in Public Health     Open Access   (Followers: 7)
Gaceta Sanitaria     Open Access   (Followers: 3)
Galen Medical Journal     Open Access  
Geospatial Health     Open Access  
Gesundheitsökonomie & Qualitätsmanagement     Hybrid Journal   (Followers: 9)
Giornale Italiano di Health Technology Assessment     Full-text available via subscription  
Global Health : Science and Practice     Open Access   (Followers: 5)
Global Health Promotion     Hybrid Journal   (Followers: 16)
Global Journal of Health Science     Open Access   (Followers: 9)
Global Journal of Public Health     Open Access   (Followers: 12)
Global Medical & Health Communication     Open Access   (Followers: 1)
Global Security : Health, Science and Policy     Open Access  
Globalization and Health     Open Access   (Followers: 5)
Hacia la Promoción de la Salud     Open Access  
Hastings Center Report     Hybrid Journal   (Followers: 3)
HEADline     Hybrid Journal  
Health & Place     Hybrid Journal   (Followers: 16)
Health & Justice     Open Access   (Followers: 5)
Health : An Interdisciplinary Journal for the Social Study of Health, Illness and Medicine     Hybrid Journal   (Followers: 7)
Health and Human Rights     Free   (Followers: 9)
Health and Social Care Chaplaincy     Hybrid Journal   (Followers: 7)
Health and Social Work     Hybrid Journal   (Followers: 55)
Health Behavior and Policy Review     Full-text available via subscription   (Followers: 2)
Health Care Analysis     Hybrid Journal   (Followers: 14)
Health Inform     Full-text available via subscription  
Health Information Management Journal     Hybrid Journal   (Followers: 16)
Health Issues     Full-text available via subscription   (Followers: 2)
Health Notions     Open Access  
Health Policy     Hybrid Journal   (Followers: 41)
Health Policy and Technology     Hybrid Journal   (Followers: 3)
Health Professional Student Journal     Open Access   (Followers: 2)
Health Promotion International     Hybrid Journal   (Followers: 21)
Health Promotion Journal of Australia : Official Journal of Australian Association of Health Promotion Professionals     Full-text available via subscription   (Followers: 10)
Health Promotion Practice     Hybrid Journal   (Followers: 15)
Health Prospect     Open Access   (Followers: 1)
Health Psychology     Full-text available via subscription   (Followers: 49)
Health Psychology Research     Open Access   (Followers: 19)
Health Psychology Review     Hybrid Journal   (Followers: 41)
Health Renaissance     Open Access  
Health Research Policy and Systems     Open Access   (Followers: 12)
Health SA Gesondheid     Open Access   (Followers: 2)
Health Science Reports     Open Access  
Health Sciences and Disease     Open Access   (Followers: 2)
Health Services Insights     Open Access   (Followers: 2)
Health Systems     Hybrid Journal   (Followers: 3)
Health Voices     Full-text available via subscription  
Health, Culture and Society     Open Access   (Followers: 13)
Health, Risk & Society     Hybrid Journal   (Followers: 11)
Healthcare     Open Access   (Followers: 1)
Healthcare in Low-resource Settings     Open Access   (Followers: 1)
Healthcare Quarterly     Full-text available via subscription   (Followers: 9)
Healthy-Mu Journal     Open Access  
HERD : Health Environments Research & Design Journal     Full-text available via subscription  
Highland Medical Research Journal     Full-text available via subscription  
Hispanic Health Care International     Full-text available via subscription  
HIV & AIDS Review     Full-text available via subscription   (Followers: 11)
Home Health Care Services Quarterly     Hybrid Journal   (Followers: 6)
Hong Kong Journal of Social Work, The     Hybrid Journal   (Followers: 2)
Hospitals & Health Networks     Free   (Followers: 4)
IEEE Journal of Translational Engineering in Health and Medicine     Open Access   (Followers: 3)
IMTU Medical Journal     Full-text available via subscription  
Indian Journal of Health Sciences     Open Access   (Followers: 2)
Indonesian Journal for Health Sciences     Open Access   (Followers: 1)
Inmanencia. Revista del Hospital Interzonal General de Agudos (HIGA) Eva Perón     Open Access  
Innovative Journal of Medical and Health Sciences     Open Access  
Institute for Security Studies Papers     Full-text available via subscription   (Followers: 5)
interactive Journal of Medical Research     Open Access  
International Health     Hybrid Journal   (Followers: 5)
International Journal for Equity in Health     Open Access   (Followers: 7)
International Journal for Quality in Health Care     Hybrid Journal   (Followers: 34)
International Journal of Applied Behavioral Sciences     Open Access   (Followers: 2)
International Journal of Behavioural and Healthcare Research     Hybrid Journal   (Followers: 8)
International Journal of Circumpolar Health     Open Access   (Followers: 1)
International Journal of Community Medicine and Public Health     Open Access   (Followers: 5)
International Journal of E-Health and Medical Communications     Full-text available via subscription   (Followers: 2)
International Journal of Environmental Research and Public Health     Open Access   (Followers: 20)
International Journal of Evidence-Based Healthcare     Hybrid Journal   (Followers: 8)
International Journal of Food Safety, Nutrition and Public Health     Hybrid Journal   (Followers: 16)
International Journal of Health & Allied Sciences     Open Access   (Followers: 3)

        1 2 3 | Last

Journal Cover Analytic Methods in Accident Research
  [SJR: 2.577]   [H-I: 7]   [4 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 2213-6657
   Published by Elsevier Homepage  [3120 journals]
  • Temporal instability and the analysis of highway accident data
    • Authors: Fred Mannering
      Pages: 1 - 13
      Abstract: Publication date: March 2018
      Source:Analytic Methods in Accident Research, Volume 17
      Author(s): Fred Mannering
      Virtually every statistical analysis of highway safety data is predicated on the assumption that the estimated model parameters are temporally stable. That is, the assumption that the effect of the determinants of accident likelihoods and resulting accident-injury severities do not change over time. This paper draws from research previously conducted in fields such as psychology, neuroscience, economics, and cognitive science to build a case for why we would not necessarily expect the effects of explanatory variables to be stable over time. The review of this literature suggests that temporal instability is likely to exist for a number of fundamental behavioral reasons, and this temporal instability is supported by the findings of several recent accident-data analyses. The paper goes on to discuss the implications of this temporal instability for contemporary accident-data modeling methods (unobserved heterogeneity, data driven, traditional, and causal inference methods) and concludes with a discussion of how temporal instability might be addressed and how its likely presence can be accounted for to better interpret accident data-analysis findings.

      PubDate: 2017-11-03T06:26:31Z
      DOI: 10.1016/j.amar.2017.10.002
      Issue No: Vol. 17 (2017)
  • A new spatial and flexible multivariate random-coefficients model for the
           analysis of pedestrian injury counts by severity level
    • Authors: Chandra R. Bhat; Sebastian Astroza; Patrícia S. Lavieri
      Pages: 1 - 22
      Abstract: Publication date: December 2017
      Source:Analytic Methods in Accident Research, Volume 16
      Author(s): Chandra R. Bhat, Sebastian Astroza, Patrícia S. Lavieri
      We propose in this paper a spatial random coefficients flexible multivariate count model to examine, at the spatial level of a census tract, the number of pedestrian injuries by injury severity level. Our model, unlike many other macro-level pedestrian injury studies in the literature, explicitly acknowledges that risk factors for different types of pedestrian injuries can be very different, as well as accounts for unobserved heterogeneity in the risk factor effects. We also recognize the multivariate nature of the injury counts by injury severity level within each census tract (as opposed to independently modeling the count of pedestrian injuries by severity level). In concrete methodological terms, our model: (a) allows a full covariance matrix for the random coefficients (constant heterogeneity, or CH, and slope heterogeneity, or SH, effects) characterizing spatial heterogeneity for each count category, (b) addresses excess zeros (or any other excess count value for that matter) within a multivariate count setting in a simple and elegant fashion, while recognizing multivariateness engendered through covariances in both the CH and SH effects, (c) accommodates spatial dependency through a spatial autoregressive lag structure, allowing for varying spatial autoregressive parameters across count categories, and (d) captures spatial drift effects through the spatial structure on the constants and the slope heterogeneity effects. To our knowledge, this is the first time that such a general spatial multivariate model has been formulated. For estimation, we use a composite marginal likelihood (CML) inference approach that is simple to implement and is based on evaluating lower-dimensional marginal probability expressions. The data for our analysis is drawn from a 2009 pedestrian crash database from the Manhattan region of New York City. Several groups of census tract-based risk factors are considered in the empirical analysis based on earlier research, including (1) socio-demographic characteristics, (2) land-use and road network characteristics, (3) activity intensity characteristics, and (4) commute mode shares and transit supply characteristics. The empirical analysis sheds light on both engineering as well as behavioral countermeasures to reduce the number of pedestrian-vehicle crashes by severity of these crashes.

      PubDate: 2017-06-07T13:04:48Z
      DOI: 10.1016/j.amar.2017.05.001
      Issue No: Vol. 16 (2017)
  • Simultaneous estimation of discrete outcome and continuous dependent
           variable equations: A bivariate random effects modeling approach with
           unrestricted instruments
    • Authors: Md Tawfiq Sarwar; Grigorios Fountas; Panagiotis Ch. Anastasopoulos
      Pages: 23 - 34
      Abstract: Publication date: December 2017
      Source:Analytic Methods in Accident Research, Volume 16
      Author(s): Md Tawfiq Sarwar, Grigorios Fountas, Panagiotis Ch. Anastasopoulos
      This paper proposes a novel methodology to simultaneously model discrete outcome (binary) and continuous dependent variables. The proposed modeling framework addresses unobserved heterogeneity by accounting for both panel effects, and for contemporaneous (cross-equation) error correlation between the two dependent variables; while, variable endogeneity is addressed through the use of unrestricted – equation specific – instruments. To illustrate the applicability of the bivariate modeling framework, SHRP2 Naturalistic Driving Study (NDS) data are used to empirically investigate the driving behavior preceding pedestrian crosswalks, in terms of brake application (binary dependent variable, binary probit specified) and speed change (continuous dependent variable, linear regression specified), simultaneously. The bivariate model is counter-imposed against its univariate binary probit and linear regression counterparts. The results of the comparative assessment demonstrate the statistical superiority of the proposed bivariate modeling approach – in terms of explanatory power, statistical fit, and forecasting accuracy – and its potential in modeling multivariate mixed dependent variables.

      PubDate: 2017-06-17T16:03:17Z
      DOI: 10.1016/j.amar.2017.05.002
      Issue No: Vol. 16 (2017)
  • Crash modeling for intersections and segments along corridors: A Bayesian
           multilevel joint model with random parameters
    • Authors: Saif A. Alarifi; Mohamed A. Abdel-Aty; Jaeyoung Lee; Juneyoung Park
      Pages: 48 - 59
      Abstract: Publication date: December 2017
      Source:Analytic Methods in Accident Research, Volume 16
      Author(s): Saif A. Alarifi, Mohamed A. Abdel-Aty, Jaeyoung Lee, Juneyoung Park
      Previous highway safety studies have focused on either intersections or roadway segments while some researchers have analyzed safety at the corridor-level. The corridor-level analysis, which aggregates intersections and roadway segments, may allow us to understand the safety problems in the wider perspective. However, it would result in losing some of the specific characteristics of intersections or roadway segments. Therefore, we proposed a multilevel joint model that explores traffic safety at the segment/intersection level, with the consideration of corridor-level variables. In addition, the variations in the roadway characteristics and/or traffic volumes across corridors have been considered using random parameters model. Nevertheless, sometimes corridors are excessively long and, thus, it is uncommon to find corridor-level variables that have fixed values for the entire length of corridors. Therefore, current corridors were divided into sub-corridors, which have similar traffic volumes and roadway characteristics, and constructed another multilevel structure based on the sub-corridor. Asa result, four Bayesian models have been estimated, and these models are multilevel Poison-lognormal (MPLN) joint models with spatial corridor and sub-corridor random effects terms and MPLN joint models with random parameters, which vary across corridors and sub-corridors. Based on a 3-years crash data from 247 signalized intersections and 208 roadway segments along 20 corridors in two counties, results showed that four-roadway segment, five-intersection, and three-corridor/sub-corridor variables were significant, and they include exposure measures and some geometric design variables. With respect to model performance, it was found that the MPLN joint model with random sub-corridor parameters provides the best fit for the data. Lastly, it is suggested to consider the proposed multilevel structure for corridor safety studies.

      PubDate: 2017-09-04T13:11:02Z
      DOI: 10.1016/j.amar.2017.08.002
      Issue No: Vol. 16 (2017)
  • Investigating the effect of spatial and mode correlations on active
           transportation safety modeling
    • Authors: Ahmed Osama; Tarek Sayed
      Pages: 60 - 74
      Abstract: Publication date: December 2017
      Source:Analytic Methods in Accident Research, Volume 16
      Author(s): Ahmed Osama, Tarek Sayed
      This paper describes the development of macro-level crash models for active modes of transportation incorporating spatial and mode correlation effects. The models are based on data from 134 traffic analysis zones (TAZs) in the City of Vancouver. Five years of cyclist and pedestrian crash data, as well as traffic exposure and large GIS data, were used to establish the macro-level crash models. The GIS data included land use, built environment, socioeconomic, bike network, and pedestrian network indicators. Full Bayesian multivariate models with and without spatial effects were developed and compared to the corresponding univariate models. The multivariate modeling approach allowed for including a different set of covariates for each modeled crash type. The univariate/multivariate crash models incorporating spatial effects consistently outperformed those that did not account for spatial effects. The correlation between pedestrian and cyclist crashes was found significant indicating the importance of accounting for the dependency among active commuters’ crash types. The mode and spatial correlations were affected by the number of the explanatory variables added to the model. Overall, the multivariate models outperformed the univariate ones, and the multivariate model incorporating spatial effects yielded the best fit among all the tested crash models. The associations between cyclist as well as pedestrian safety and various zones’ characteristics were also investigated in this study.

      PubDate: 2017-09-16T16:45:21Z
      DOI: 10.1016/j.amar.2017.08.003
      Issue No: Vol. 16 (2017)
  • Impact of road-surface condition on rural highway safety: A multivariate
           random parameters negative binomial approach
    • Authors: Sikai Chen; Tariq Usman Saeed; Samuel Labi
      Pages: 75 - 89
      Abstract: Publication date: December 2017
      Source:Analytic Methods in Accident Research, Volume 16
      Author(s): Sikai Chen, Tariq Usman Saeed, Samuel Labi
      Recent studies have begun to shed more light on the crashes experienced on rural roads by examining the influence of a road’s pavement surface condition. In a bid to contribute to this growing body of knowledge and to facilitate comprehensive evaluation of pavement maintenance projects, this paper explores the safety effects of the pavement condition of rural roads. The paper tests the hypotheses that pavement roughness generally has a non-trivial residual impact on safety outcomes and that the magnitude and direction of these impacts differ across road segments. To explore these hypotheses, the paper presents crash frequency models for three levels of crash severity and also across five levels of road surface condition. The developed models use the multivariate random parameters negative binomial specification to account for the unobserved heterogeneity and correlation among the different levels of crash severity. The model results suggest that for pavements in fair or good condition, the surface condition parameter has fixed effects on the crash frequency, irrespective of the crash severity level. However, for pavements in poor condition, the surface condition variable in the crash model has a significant random parameter that is normally distributed. The positive portions of the parameter density function suggest that higher roughness (poorer condition) generally increases the expected crash frequency, likely because drivers may lose control of their vehicles. The negative portions suggest that within that condition range, higher surface roughness is generally associated with a lower expected crash frequency, likely because drivers are generally likely to drive more carefully on pavements in very poor condition (a manifestation of risk-compensation behavior). The developed models can help highway engineers quantify not only the safety benefits of road resurfacing projects but also the safety consequences of worsening road surface conditions arising from delay of pavement maintenance.

      PubDate: 2017-09-21T18:36:14Z
      DOI: 10.1016/j.amar.2017.09.001
      Issue No: Vol. 16 (2017)
  • Gas dynamic analogous exposure approach to interaction intensity in
           multiple-vehicle crash analysis: Case study of crashes involving taxis
    • Authors: Fanyu Meng; Wai Wong; S.C. Wong; Xin Pei; Y.C. Li; Helai Huang
      Pages: 90 - 103
      Abstract: Publication date: December 2017
      Source:Analytic Methods in Accident Research, Volume 16
      Author(s): Fanyu Meng, Wai Wong, S.C. Wong, Xin Pei, Y.C. Li, Helai Huang
      Exposure is a frequency measure of being in situations in which crashes could occur. In modeling multiple-vehicle crash frequency, traditional exposure measures, such as vehicle kilometrage and travel time, may not be sufficiently representative because they may include situations in which vehicles rarely meet each other and multiple-vehicle crashes can never happen. The meeting frequency of vehicles should be a better exposure measure in such cases. This study aims to propose a novel Gas Dynamic Analogous Exposure (GDAE) to model multiple-vehicle crash frequency. We analogize the meeting frequency of vehicles with the meeting frequency of gas molecules because both systems consider the numbers of the meetings of discrete entities. A meeting frequency function of vehicles is derived based on the central idea of the classical collision theory in physical chemistry with consideration of constrained vehicular movement by the road alignments. The GDAE is then formulated on the basis of the major factors that contribute to the meeting frequency of vehicles. The proposed GDAE is a more representative proxy exposure measure in modeling of multiple-vehicle crash frequency because it further investigates and provides insight into the physics of the vehicle meeting mechanism. To demonstrate the applicability of the GDAE, zonal crash frequency models are constructed on the basis of multiple-vehicle crashes involving taxis in 398 zones of Hong Kong in 2011. The GDAE outperforms the conventional time exposure in multiple-vehicle crash modeling. To account for any unobservable heterogeneity and to cope with the over-dispersed count data, a random-parameter negative binomial model is established. Explanatory factors that contribute to the zonal multiple-vehicle crash risk involving taxis are identified. The proposed GDAE is a promising exposure measure for modeling multiple-vehicle crash frequency.

      PubDate: 2017-10-19T04:02:37Z
      DOI: 10.1016/j.amar.2017.09.003
      Issue No: Vol. 16 (2017)
  • Roadway classifications and the accident injury severities of
           heavy-vehicle drivers
    • Authors: Jason Anderson; Salvador Hernandez
      Pages: 17 - 28
      Abstract: Publication date: September 2017
      Source:Analytic Methods in Accident Research, Volume 15
      Author(s): Jason Anderson, Salvador Hernandez
      Previous heavy-vehicle (a truck with a gross vehicle weight rating greater than 10,000 pounds) injury severity studies have disaggregated data by factors such as urban/rural and time-of-day, yet a focus on contributing factors by roadway classification is lacking. Taking this into consideration, the current study aims to extend traditional heavy-vehicle driver injury severity analyses, through the application of a mixed logit modeling framework, by determining statistically significant injury severity contributing factors by roadway classification. In the course of identifying statistically significant injury severity factors, a parameter transferability test is conducted to determine if roadway classifications need to be considered separately for safety analyses. Empirical results show that roadway classifications need be modeled separately with a high level of confidence, as the estimated parameters are statistically different by classification based on corresponding chi-square statistics and degrees of freedom. The majority of significant contributing factors are exclusive to a specific road classification, however, two factors were found to impact injury severity regardless of classification while some factors were significant for two classifications. Findings from this study can prompt future work to focus on injury severity, as well as other safety measures, by roadway classification and/or other subpopulations within crash datasets.

      PubDate: 2017-05-09T08:30:31Z
      DOI: 10.1016/j.amar.2017.04.002
      Issue No: Vol. 15 (2017)
  • Multivariate space-time modeling of crash frequencies by injury severity
    • Authors: Xiaoxiang Ma; Suren Chen; Feng Chen
      Pages: 29 - 40
      Abstract: Publication date: September 2017
      Source:Analytic Methods in Accident Research, Volume 15
      Author(s): Xiaoxiang Ma, Suren Chen, Feng Chen
      Road traffic crashes threaten thousands of drivers every day and significant efforts have been put forth to reduce the number and mitigate the impacts of traffic crashes. Although the last decade has witnessed substantial methodological improvements in crash prediction modelling, several methodological challenges still remain in terms of predicting crash frequencies of different injury severity levels. These challenges include spatial correlation and/or heterogeneity, temporal correlation and/or heterogeneity, and correlations between crash frequencies of different injury severity level. A framework of Bayesian multivariate space-time model is developed to address these challenges. A series of multivariate space-time models are proposed under the Full Bayesian framework with different assumptions on the spatial and temporal random effects. In addition to the ability to consider both temporal and spatial trends, the proposed framework is also capable of addressing complex correlations between crash types. It allows the underlying unobserved heterogeneity to be better captured and enables borrowing strength across spatial units and time points, as well as over crash types. The proposed methodology is illustrated using one-year daily traffic crash data from the mountainous interstate highway I70 in Colorado, which is categorized into no injury crash and injury crash. The results show that multivariate space-time model outperforms other alternatives, including multivariate random effects model and multivariate spatial models. The model comparison results highlight the importance to properly account for spatial effects, temporal effects and correlations between crash types.

      PubDate: 2017-06-22T17:27:46Z
      DOI: 10.1016/j.amar.2017.06.001
      Issue No: Vol. 15 (2017)
  • A negative binomial crash sum model for time invariant heterogeneity in
           panel crash data: Some insights
    • Authors: Ghasak I.M.A. Mothafer; Toshiyuki Yamamoto; Venkataraman N. Shankar
      Pages: 1 - 9
      Abstract: Publication date: June 2017
      Source:Analytic Methods in Accident Research, Volume 14
      Author(s): Ghasak I.M.A. Mothafer, Toshiyuki Yamamoto, Venkataraman N. Shankar
      This paper presents a negative binomial crash sum model as an alternative for modeling time invariant heterogeneity in short panel crash data. Time invariant heterogeneity arising through multiple years of observation for each segment is viewed as a common unobserved effect at the segment level, and typically treated with panel models involving fixed or random effects. Random effects model unobserved heterogeneity through the error term, typically following a gamma or normal distribution. We take advantage of the fact that gamma heterogeneity in a multi-period Poisson count modeling framework is equivalent to a negative binomial distribution for a dependent variable which is the summation of crashes across years. The Poisson panel model referred to in this paper is the random effects Poisson gamma (REPG). In the REPG model, the dependent variable is an annual number of a specific crash type. The multi-year crash sum model is a negative binomial (NB) model that is based on three consecutive years of crash data (2005–2007). In the multi-year crash sum model, the dependent variable is the sum of crashes of a specific type for the three-year period. Four categories (in addition to total crashes) of crash types are considered in this study including rear end, sideswipe, fixed objects and all-other types. The empirical results show that when time effects are insignificant in short panels such as the one used in this study, the three-year crash sum model is a computationally simpler alternative to a panel model for modeling time invariant heterogeneity while imposing fewer data requirements such as annual measurements.

      PubDate: 2017-01-22T22:41:36Z
      DOI: 10.1016/j.amar.2016.12.003
      Issue No: Vol. 14 (2017)
  • A multivariate spatial model of crash frequency by transportation modes
           for urban intersections
    • Authors: Helai Huang; Hanchu Zhou; Jie Wang; Fangrong Chang; Ming Ma
      Pages: 10 - 21
      Abstract: Publication date: June 2017
      Source:Analytic Methods in Accident Research, Volume 14
      Author(s): Helai Huang, Hanchu Zhou, Jie Wang, Fangrong Chang, Ming Ma
      This study proposes a multivariate spatial model to simultaneously analyze the occurrence of motor vehicle, bicycle and pedestrian crashes at urban intersections. The proposed model can account for both the correlation among different modes involved in crashes at individual intersections and spatial correlation between adjacent intersections. According to the results of the model comparison, multivariate spatial model outperforms the univariate spatial model and the multivariate model in the goodness-of-fit. The results confirm the highly correlated heterogeneous residuals in modeling crash risk among motor vehicles, bicycles and pedestrians. In regard to spatial correlation, the estimates of variance for spatial correlations of all three crash modes in the multivariate and univariate models are statistically significant; however, the correlations for spatial residuals between different crash modes at adjacent sites are not statistically significant. More interestingly, the results show that the proportion of variation explained by the spatial effects is much higher for motor vehicle crashes than for bicycle and pedestrian crashes, which indicates spatial correlations between adjacent intersections are significantly different between the motor vehicle and non-motorized modes.

      PubDate: 2017-01-22T22:41:36Z
      DOI: 10.1016/j.amar.2017.01.001
      Issue No: Vol. 14 (2017)
  • A Modified Rank Ordered Logit model to analyze injury severity of
           occupants in multivehicle crashes
    • Authors: Shelley Bogue; Rajesh Paleti; Lacramioara Balan
      Pages: 22 - 40
      Abstract: Publication date: June 2017
      Source:Analytic Methods in Accident Research, Volume 14
      Author(s): Shelley Bogue, Rajesh Paleti, Lacramioara Balan
      The current study developed a simultaneous model of injury severity outcomes of all occupants in multi-vehicle crashes including all the drivers and the passengers of all vehicles involved in a crash. Specifically, a Modified Rank Ordered Logit (MROL) methodology that can predict the relative order of occupant injury severity as well as the actual injury severity was developed. The final model captures the effects of several key occupant, vehicle, and accident level variables on four possible levels of injury severity. The results indicate the presence of accident-specific unobserved factors that influence the severity outcomes of all people involved in the crash as well as unobserved heterogeneity in the effect of key covariates including occupant’s gender and speed limit. The performance of the MROL model was compared with the traditional mixed multinomial logit (MMNL) model that is the most commonly used model for injury severity analysis. Overall, the results demonstrate superior predictive ability of the MROL model in comparison to the MMNL model. The traditional MMNL model performed satisfactory in terms of replicating the simple shares of different injury severity levels across all occupants. However, the performance of the MMNL model dropped significantly when the observed and predicted shares were compared for combinations of injury severity levels among crashes involving multiple occupants. Lastly, elasticity effects were computed to demonstrate considerably different policy implications of the MROL and MMNL models.

      PubDate: 2017-03-13T00:29:02Z
      DOI: 10.1016/j.amar.2017.03.001
      Issue No: Vol. 14 (2017)
  • The effect of passengers on driver-injury severities in single-vehicle
           crashes: A random parameters heterogeneity-in-means approach
    • Authors: Ali Behnood; Fred Mannering
      Pages: 41 - 53
      Abstract: Publication date: June 2017
      Source:Analytic Methods in Accident Research, Volume 14
      Author(s): Ali Behnood, Fred Mannering
      This paper seeks to investigate the effects of passengers on driver-injury severities. Using single-vehicle crashes, a random parameters logit model with heterogeneity in parameter means is estimated to explore the differences in driver-injury severities in three distinct subgroups; vehicles with one occupant (driver-only), vehicles with two occupants (driver and a passenger), and vehicles with three occupants (driver and two passengers). In addition to considering age, gender and the presence of the passenger(s), a wide range of variables that potentially affect driver-injury severity were considered, including weather conditions, roadway characteristics, vehicle characteristics and driver attributes. Estimation results show that both the age and the gender of the passenger(s) significantly affected driver-injury severities. The findings of this research point toward the need to further study the potentially complex interactions between drivers and passengers.

      PubDate: 2017-05-18T09:48:32Z
      DOI: 10.1016/j.amar.2017.04.001
      Issue No: Vol. 14 (2017)
  • The effect of variations in spatial units on unobserved heterogeneity in
           macroscopic crash models
    • Authors: Richard Amoh-Gyimah; Meead Saberi; Majid Sarvi
      Pages: 28 - 51
      Abstract: Publication date: March 2017
      Source:Analytic Methods in Accident Research, Volume 13
      Author(s): Richard Amoh-Gyimah, Meead Saberi, Majid Sarvi
      Macroscopic safety models establish a relationship between crashes and the contributing factors in a defined spatial unit. Negative binomial (NB) and Bayesian negative binomial models with conditional autoregressive prior (CAR) are techniques widely used to establish this relationship. However, these models do not account for unobserved heterogeneity and their output is global and fixed irrespective of the spatial unit of the analysis. There is a timely need to understand how variations in spatial units affect unobserved heterogeneity. This study uses two advanced modeling techniques, the random parameter negative binomial (RPNB) and the semi-parametric geographically weighted Poisson regression (S-GWPR), to investigate whether explanatory variables found to be significant and random in one spatial aggregation will remain significant and random when another spatial aggregation is used. The key finding is that variations in spatial units do have an impact on unobserved heterogeneity. We also found that variations in spatial units have a greater impact on unobserved heterogeneity in the RPNB models compared to the S-GWPR models. We found that the S-GWPR model performs better than the RPNB model with the lowest value of mean absolute deviation (MAD) and Akaiki information criterion (AIC) but the two modeling techniques produce similar results in terms of the sign of the coefficients across the selected spatial units of analysis. Overall, the study provides a methodological basis for assessing the impact of spatial units on unobserved heterogeneity.

      PubDate: 2017-01-22T22:41:36Z
      DOI: 10.1016/j.amar.2016.11.001
      Issue No: Vol. 13 (2017)
  • The effect of long term non-invasive pavement deterioration on accident
           injury-severity rates: A seemingly unrelated and multivariate equations
    • Authors: Md Tawfiq Sarwar; Panagiotis Ch. Anastasopoulos
      Pages: 1 - 15
      Abstract: Publication date: March 2017
      Source:Analytic Methods in Accident Research, Volume 13
      Author(s): Md Tawfiq Sarwar, Panagiotis Ch. Anastasopoulos
      This paper seeks to measure the effect of long term non-invasive pavement deterioration on accident injury-severity rates, and demonstrate the potential of considering safety as one of the criteria in the pavement management decision making process. Using data from Indiana, a system of seemingly unrelated regression equations (SURE) is estimated to predict pavement deterioration curves over a 30-year projection period based on three commonly used pavement performance indicators. The annual predictors of the pavement roughness, rutting depth, and pavement condition rating are then used in a multivariate tobit equations model of vehicle accident injury-severity rates. The results provide the expected change of the no injury, injury, and fatality rates, due to the non-invasive pavement deterioration, and are compared to a budget-unrestricted scenario under which rehabilitation occurs routinely. Even though the aim of the paper is not to provide an optimal pavement management program, the findings suggest that safety should be considered as one of the decision making criteria.

      PubDate: 2016-11-19T06:27:33Z
      DOI: 10.1016/j.amar.2016.10.003
      Issue No: Vol. 13 (2016)
  • Using a flexible multivariate latent class approach to model correlated
           outcomes: A joint analysis of pedestrian and cyclist injuries
    • Authors: Shahram Heydari; Liping Fu; Luis F. Miranda-Moreno; Lawrence Joseph
      Pages: 16 - 27
      Abstract: Publication date: March 2017
      Source:Analytic Methods in Accident Research, Volume 13
      Author(s): Shahram Heydari, Liping Fu, Luis F. Miranda-Moreno, Lawrence Joseph
      Several recent transportation safety studies have indicated the importance of accounting for correlated outcomes, for example, among different crash types, including differing injury-severity levels. In this paper, we discuss inference for such data by introducing a flexible Bayesian multivariate model. In particular, we use a Dirichlet process mixture to keep the dependence structure unconstrained, relaxing the usual homogeneity assumptions. The resulting model collapses into a latent class multivariate model that is in the form of a flexible mixture of multivariate normal densities for which the number of mixtures (latent components) not only can be large but also can be inferred from the data as part of the analysis. Therefore, besides accounting for correlation among crash types through a heterogeneous correlation structure, the proposed model helps address unobserved heterogeneity through its latent class component. To our knowledge, this is the first study to propose and apply such a model in the transportation literature. We use the model to investigate the effects of various factors such as built environment characteristics on pedestrian and cyclist injury counts at signalized intersections in Montreal, modeling both outcomes simultaneously. We demonstrate that the homogeneity assumption of the standard multivariate model does not hold for the dataset used in this study. Consequently, we show how such a spurious assumption affects predictive performance of the model and the interpretation of the variables based on marginal effects. Our flexible model better captures the underlying complex structure of the correlated data, resulting in a more accurate model that contributes to a better understanding of safety correlates of non-motorist road users. This in turn helps decision-makers in selecting more appropriate countermeasures targeting vulnerable road users, promoting the mobility and safety of active modes of transportation.

      PubDate: 2016-12-25T16:07:29Z
      DOI: 10.1016/j.amar.2016.12.002
      Issue No: Vol. 13 (2016)
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
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Fax: +00 44 (0)131 4513327
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