scholarly journals Estimation of side-impact crash risk at signalized intersections

2021 ◽  
Author(s):  
Dewan Masul Karim
Keyword(s):  
Negative Binomial ◽  
Safety Management ◽  
Likelihood Estimation ◽  
Negative Binomial Regression ◽  
Signalized Intersections ◽  
Side Impact ◽  
Crash Risk ◽  
Estimation Of Parameters ◽  
Explanatory Variables ◽  
The Relationship

Side impact accidents are considered to be the most dangerous of all types of intersection accidents due to their high severity. In-depth investigation of accident occurrence could be a valuable means of mitigating these accidents. Based on the relationship between the distribution of disturbances near intersections and driers reactions, this study developed a logic for three major types of signalized intersections side impact crashes were considered for this study - right-angle, and left and right-turning crashes. The study developed models to understand the relationship between accident frequency and some explanatory variables that represent, driver, vehicle, traffic flow and intersection design characteristics. Negative binomial regression with maximum likelihood estimation of parameters is applied to address the overdispersion usually found in accident count data. The models explain the mechanism of side-impact accident occurrence and could be used to assist safety management agencies to devise countermeasures aimed at divers, and the physical roadway environment.

scholarly journals Estimation of side-impact crash risk at signalized intersections

2021 ◽  
Author(s):  
Dewan Masul Karim
Keyword(s):  
Negative Binomial ◽  
Safety Management ◽  
Likelihood Estimation ◽  
Negative Binomial Regression ◽  
Signalized Intersections ◽  
Side Impact ◽  
Crash Risk ◽  
Estimation Of Parameters ◽  
Explanatory Variables ◽  
The Relationship

Side impact accidents are considered to be the most dangerous of all types of intersection accidents due to their high severity. In-depth investigation of accident occurrence could be a valuable means of mitigating these accidents. Based on the relationship between the distribution of disturbances near intersections and driers reactions, this study developed a logic for three major types of signalized intersections side impact crashes were considered for this study - right-angle, and left and right-turning crashes. The study developed models to understand the relationship between accident frequency and some explanatory variables that represent, driver, vehicle, traffic flow and intersection design characteristics. Negative binomial regression with maximum likelihood estimation of parameters is applied to address the overdispersion usually found in accident count data. The models explain the mechanism of side-impact accident occurrence and could be used to assist safety management agencies to devise countermeasures aimed at divers, and the physical roadway environment.

scholarly journals Public or Private Religiosity: Which Is Protective for Adolescent Substance Use and by What Pathways?

2016 ◽  
Vol 49 (2) ◽  
pp. 228-253 ◽  
Author(s):  
Christopher P. Salas-Wright ◽  
Michael G. Vaughn ◽  
Brandy R. Maynard ◽  
Trenette T. Clark ◽  
Susanna Snyder
Keyword(s):  
Substance Use ◽  
Sensation Seeking ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
National Sample ◽  
Adolescent Substance Use ◽  
Public And Private ◽  
Adolescent Substance ◽  
The Relationship ◽  
Private Religiosity

While it is well understood that adolescent religiosity is associated with the use and abuse of licit and illicit substances, few studies have revealed the pathways through which religiosity buffers youth against involvement in such behavior. The aim of this study is to examine the complexity of the relationships between religiosity, sensation seeking, injunctive norms, and adolescent substance use. Using a national sample of adolescents ( N = 18,614), negative binomial regression and path analysis were used to examine the various components of the relationship between religiosity and the use of cigarettes, alcohol, and marijuana. Results indicate that private religiosity moderates the relationship between key risk factors and substance use. Public and private religiosity were associated with tolerant injunctive substance use norms which, in turn, were associated with substance use. Implications for research and theory related to religiosity and adolescent substance use are discussed.

scholarly journals Analysis of Nonsevere Crashes on Two- and Four-Lane Urban and Rural Highways: Effects of Wet Pavement Surface Condition

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Aschalew Kassu ◽  
Michael Anderson
Keyword(s):  
Negative Binomial ◽  
Surface Condition ◽  
Negative Binomial Regression ◽  
Segment Length ◽  
Mean Values ◽  
Rural Highways ◽  
Explanatory Variables ◽  
Crash Data ◽  
Pavement Surface ◽  
Binomial Regression

This study examines the effects of wet pavement surface conditions on the likelihood of occurrences of nonsevere crashes in two- and four-lane urban and rural highways in Alabama. Initially, sixteen major highways traversing across the geographic locations of the state were identified. Among these highways, the homogenous routes with equal mean values, variances, and similar distributions of the crash data were identified and combined to form crash datasets occurring on dry and wet pavements separately. The analysis began with thirteen explanatory variables covering engineering, environmental, and traffic conditions. The principal terms were statistically identified and used in a mathematical crash frequency models developed using Poisson and negative binomial regression models. The results show that the key factors influencing nonsevere crashes on wet pavement surfaces are mainly segment length, traffic volume, and posted speed limits.

scholarly journals NATO between Exclusivity and Inclusivity: Measuring NATO’s Partnerships

2021 ◽  
pp. 1-32
Author(s):  
Branislav Mičko
Keyword(s):  
Human Rights ◽  
Fixed Effects ◽  
International Institutions ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Original Dataset ◽  
Strategic Approach ◽  
Binomial Regression ◽  
The Given ◽  
The Relationship

Building on an original dataset, this article focuses on the interactions between NATO and its declared worldwide partners. It argues that the analysis of these interactions can reveal NATO’s strategic approach to partnerships, but it can also provide a tool for its classification as an organisation that is either exclusive – defined by the focus on defence of its members, or inclusive – emphasising the global protection of democracies and human rights. The relationship between types of interactions and NATO categorisation is estimated using an unconditional negative binomial regression with fixed effects as well as a within-between (hybrid) model. Furthermore, they are illustrated on two brief case studies of Sweden and Japan. The results of the study suggest that NATO engages primarily with countries that are powerful relative to their neighbourhood, even though they are not the most powerful among the partners. The given country’s level of democracy, integration into the international institutions, and stability, do not seem to play any overarching role here.

scholarly journals Handling of Overdispersion in the Poisson Regression Model with Negative Binomial for the Number of New Cases of Leprosy in Java

2021 ◽  
Vol 5 (1) ◽  
pp. 1-13
Author(s):  
Yopi Ariesia Ulfa ◽  
Agus M Soleh ◽  
Bagus Sartono
Keyword(s):  
Regression Model ◽  
Poisson Regression ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Explanatory Variables ◽  
Binomial Regression ◽  
Directorate General ◽  
The Republic ◽  
And Control

Based on data from the Directorate General of Disease Prevention and Control of the Ministry of Health of the Republic of Indonesia, in 2017, new leprosy cases that emerged on Java Island were the highest in Indonesia compared to the number of events on other islands. The purpose of this study is to compare Poisson regression to a negative binomial regression model to be applied to the data on the number of new cases of leprosy and to find out what explanatory variables have a significant effect on the number of new cases of leprosy in Java. This study's results indicate that a negative binomial regression model can overcome the Poisson regression model's overdispersion. Variables that significantly affect the number of new cases of leprosy based on the results of negative binomial regression modeling are total population, percentage of children under five years who had immunized with BCG, and percentage of the population with sustainable access to clean water.

scholarly journals The Relationship Between Social Vulnerability and COVID-19 Incidence Among Louisiana Census Tracts

2021 ◽  
Vol 8 ◽  
Author(s):  
Erin N. Biggs ◽  
Patrick M. Maloney ◽  
Ariane L. Rung ◽  
Edward S. Peters ◽  
William T. Robinson
Keyword(s):  
Population Density ◽  
Social Vulnerability ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Vulnerability Index ◽  
Social Vulnerability Index ◽  
Census Tracts ◽  
Control And Prevention ◽  
Choropleth Maps ◽  
The Relationship

Objective: To examine the association between the Centers for Disease Control and Prevention (CDC)'s Social Vulnerability Index (SVI) and COVID-19 incidence among Louisiana census tracts.Methods: An ecological study comparing the CDC SVI and census tract-level COVID-19 case counts was conducted. Choropleth maps were used to identify census tracts with high levels of both social vulnerability and COVID-19 incidence. Negative binomial regression with random intercepts was used to compare the relationship between overall CDC SVI percentile and its four sub-themes and COVID-19 incidence, adjusting for population density.Results: In a crude stratified analysis, all four CDC SVI sub-themes were significantly associated with COVID-19 incidence. Census tracts with higher levels of social vulnerability were associated with higher COVID-19 incidence after adjusting for population density (adjusted RR: 1.52, 95% CI: 1.41-1.65).Conclusions: The results of this study indicate that increased social vulnerability is linked with COVID-19 incidence. Additional resources should be allocated to areas of increased social disadvantage to reduce the incidence of COVID-19 in vulnerable populations.

scholarly journals The Relationship between Near-Repeat Street Robbery and the Environment: Evidence from Malmö, Sweden

2020 ◽  
Vol 9 (4) ◽  
pp. 188
Author(s):  
Markus Rasmusson ◽  
Marco Helbich
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Socioeconomic Indicators ◽  
Law Enforcement Agencies ◽  
Environmental Characteristics ◽  
Binomial Regression ◽  
Using Data ◽  
Near Repeat ◽  
The Relationship ◽  
Crime Event

Near-repeat crime refers to a pattern whereby one crime event is soon followed by a similar crime event at a nearby location. Existing research on near-repeat crime patterns is inconclusive about where near-repeat patterns emerge and which physical and social factors influence them. The present research addressed this gap by examining the relationship between initiator events (i.e., the first event in a near-repeat pattern) and environmental characteristics to estimate where near-repeat patterns are most likely to emerge. A two-step analysis was undertaken using data on street robberies reported in Malmö, Sweden, for the years 2006–15. After determining near-repeat patterns, we assessed the correlations between initiator events and criminogenic places and socioeconomic indicators using a negative binomial regression at a street segment level. Our results show that both criminogenic places and socioeconomic indicators have a significant influence on the spatial variation of initiator events, suggesting that environmental characteristics can be used to explain the emergence of near-repeat patterns. Law enforcement agencies can utilize the findings in efforts to prevent further street robberies from occurring.

scholarly journals The relationship between fleas and small mammals in households of the Western Yunnan Province, China

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jia-Xiang Yin ◽  
Xiao-Ou Cheng ◽  
Yun-Yan Luo ◽  
Qiu-Fang Zhao ◽  
Zhao-Fei Wei ◽  
...  
Keyword(s):  
Small Mammals ◽  
Host Species ◽  
Yunnan Province ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Strong Relationship ◽  
Negative Binomial Regression Model ◽  
Small Male ◽  
Western Yunnan ◽  
The Relationship

Abstract The Yunnan province has one of the most serious outbreaks of the plague epidemic in China. Small mammals and fleas are risk factors for the occurrence of plague in commensal plague foci. Understanding the relationship between fleas and small mammals will help control fleas and prevent the onset of the plague. Four hundred and twenty-one small mammals, belonging to 9 species, were captured. Of these, 170 small mammals (40.4%) were found infested with fleas. A total of 992 parasitic fleas (including 5 species) were collected. The number of Leptopsylla segnis and Xenopsylla cheopis accounted for 91.03% (903/992). The final multiple hurdle negative binomial regression model showed that when compared with Rattus tanezumi, the probability of flea infestation with Mus musculus as well as other host species decreased by 58% and 99%, respectively, while the number of flea infestations of the other host species increased by 4.71 folds. The probability of flea prevalence in adult hosts increased by 74%, while the number of fleas decreased by 76%. The number of flea infestations in small male mammals increased by 62%. The number of fleas in small mammals weighing more than 59 g has been multiplied by about 4. R. tanezumi is the predominant species in households in the west Yunnan province, while L.segnis and X. cheopis were dominant parasitic fleas. There is a strong relationship between the abundance of fleas and the characteristics of small mammals (e.g. Species, age, sex, and body weight).

Examining Safety on Two-Lane and Multilane Highways in Consideration of Access Spacing

2019 ◽  
Vol 2673 (11) ◽  
pp. 388-397
Author(s):  
Raha Hamzeie ◽  
Megat-Usamah Megat-Johari ◽  
Iftin Thompson ◽  
Timothy P. Barrette ◽  
Trevor Kirsch ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Random Effect ◽  
Management Strategies ◽  
Negative Binomial Regression ◽  
Access Point ◽  
Management Policy ◽  
Crash Risk ◽  
Access Management ◽  
Crash Data ◽  
Crash Rates

Access management strategies, such as the introduction of minimum access point spacing criteria and turning movement restrictions, have been shown to be important elements in optimizing the operational and safety performance of roadway segments. The relationship between safety and these types of access policies is a complex issue, and the impacts of such features on traffic crashes is critical to the development of appropriate access management strategies. The purpose of this study was to provide a quantitative evaluation of how crash risk on multilane and two-lane highways varies with respect to access spacing in support of the development of a revised access management policy. Data were obtained for approximately 1,247 and 5,795 mi of segments across multilane and two-lane highways, respectively. Crash data were obtained for a five-year period from 2012 to 2016 and a series of random effect negative binomial regression models were estimated for each facility to examine the association between crash frequency, access point spacing, and traffic volume. For both facility types, crashes were found to increase consistently as the average spacing of access points along road segments decreased. Crash rates were highest when consecutive accesses were within 150 ft of one another and the frequency of crashes decreased substantively as spacing was increased to 300 ft and, particularly, 600 ft. With spacing beyond 600 ft, crash rates continued to decrease, although these improvements were less pronounced than at the lower range of values. These findings were generally consistent on multilane and two-lane highways.

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