Homeland Violence and Diaspora Insecurity: An Analysis of Israel and American Jewry

2019 ◽  
Vol 13 (1) ◽  
pp. 1-27
Author(s):  
Ayal K. Feinberg
Keyword(s):  
United States ◽  
Fixed Effects ◽  
Hate Crime ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
The United States ◽  
Hate Crimes ◽  
Federal Bureau Of Investigation ◽  
American Jewry ◽  
Binomial Regression

AbstractJews and Jewish institutions have suffered the majority of reported religion-motivated hate crimes in the United States for nearly two decades. According to the Federal Bureau of Investigation (FBI), in 2014 the 609 reported anti-Semitic incidents made up 59% of all religious bias hate crimes alone. Rates of reported anti-Semitic hate crimes vary considerably over the course of a year. Yet, little scholarly attention has been given to what factors cause reported anti-Semitic hate crimes to fluctuate so substantially in the United States. This paper hypothesizes that violent Israeli military engagements are critical in explaining weekly surges of reported anti-Semitic hate crimes. Utilizing FBI hate crime data from 2001 to 2014 and fixed effects negative binomial regression models, consistent findings underscore that violent Israeli military engagements significantly increase the likelihood of a state reporting anti-Semitic hate crime. Most dramatically, their occurrence increases the likelihood of reported hate crime intimidating individuals or characterized as violent by nearly 35%. This paper underscores that homeland perpetrated violence can directly impact the security of diaspora communities.

scholarly journals Application of Discrete Regression Models for Analyzing K-8 Students Nonchronic Absenteeism in the United States

2021 ◽  
Vol 10 (4) ◽  
pp. 127
Author(s):  
Khairul Islam ◽  
Tanweer J. Shapla
Keyword(s):  
United States ◽  
Regression Models ◽  
Negative Binomial ◽  
Descriptive Analysis ◽  
Negative Binomial Regression ◽  
The United States ◽  
Chronic Absenteeism ◽  
Factors Affecting ◽  
National Crisis ◽  
Binomial Regression

Absenteeism is a national crisis in the United States, and must be addressed adequately at the early stages or at its onset, to prevent consequential disaster and burden due to absenteeism. A pervasive and persuasive nonchronic absenteeism results in chronic absenteeism, and causes severe damage to students’ life, schools and societies. While a good number of articles address various issues relating to chronic absenteeism, no evidence of research exists investigating nonchronic absenteeism. The aim of this article is to investigate factors affecting nonchronic absenteeism in K-8 students in the United States by applying discrete regression models. Initially, we investigate K-8 students nonchronic absenteeism discrepancies due to socio-demographic and parental involvement factors via descriptive analysis and then employ Poisson and negative binomial regression models for exploring significant factors of K-8 nonchronic absenteeism. The findings of this study will be of great use to stakeholders in developing appropriate incentive measures for reducing nonchronic absenteeism early and thereby reducing chronic absenteeism.

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 Retracted: Analysis of the Strength of Legal Firearms Restrictions for Perpetrators of Domestic Violence and Their Associations With Intimate Partner Homicide

2017 ◽  
Vol 187 (7) ◽  
pp. 1449-1455 ◽  
Author(s):  
April M Zeoli ◽  
Alexander McCourt ◽  
Shani Buggs ◽  
Shannon Frattaroli ◽  
David Lilley ◽  
...  
Keyword(s):  
Domestic Violence ◽  
Fixed Effects ◽  
Negative Binomial ◽  
State Level ◽  
Negative Binomial Regression ◽  
Intimate Partner ◽  
Restraining Order ◽  
Level Data ◽  
Binomial Regression ◽  
Firearms Restrictions

Abstract In this research, we estimate the association of firearm restrictions for domestic violence offenders with intimate partner homicides (IPHs) on the basis of the strength of the policies. We posit that the association of firearm laws with IPHs depends on the following characteristics of the laws: 1) breadth of coverage of high-risk individuals and situations restricted; 2) power to compel firearm surrender or removal from persons prohibited from having firearms; and 3) systems of accountability that prevent those prohibited from doing so from obtaining guns. We conducted a quantitative policy evaluation using annual state-level data from 1980 through 2013 for 45 US states. Based on the results of a series of robust, negative binomial regression models with state fixed effects, domestic violence restraining order firearm-prohibition laws are associated with 10% reductions in IPH. Statistically significant protective associations were evident only when restraining order prohibitions covered dating partners (−11%) and ex parte orders (−12%). Laws prohibiting access to those convicted of nonspecific violent misdemeanors were associated with a 24% reduction in IPH rates; there was no association when prohibitions were limited to domestic violence. Permit-to-purchase laws were associated with 10% reductions in IPHs. These findings should inform policymakers considering laws to maximize protections against IPH.

Using complementary methods to test whether marriage limits men's antisocial behavior

2013 ◽  
Vol 25 (1) ◽  
pp. 65-77 ◽  
Author(s):  
Sara R. Jaffee ◽  
Caitlin McPherran Lombardi ◽  
Rebekah Levine Coley
Keyword(s):  
United States ◽  
Antisocial Behavior ◽  
Representative Sample ◽  
Fixed Effects ◽  
Negative Binomial ◽  
The United States ◽  
Complementary Methods ◽  
Married Men ◽  
Nationally Representative ◽  
The Relationship

AbstractMarried men engage in significantly less antisocial behavior than unmarried men, but it is not clear whether this reflects a causal relationship. Instead, the relationship could reflect selection into marriage whereby the men who are most likely to marry (men in steady employment with high levels of education) are the least likely to engage in antisocial behavior. The relationship could also be the result of reverse causation, whereby high levels of antisocial behavior are a deterrent to marriage rather than the reverse. Both of these alternative processes are consistent with the possibility that some men have a genetically based proclivity to become married, known as an active genotype–environment correlation. Using four complementary methods, we tested the hypothesis that marriage limits men's antisocial behavior. These approaches have different strengths and weaknesses and collectively help to rule out alternative explanations, including active genotype–environment correlations, for a causal association between marriage and men's antisocial behavior. Data were drawn from the in-home interview sample of the National Longitudinal Study of Adolescent Health, a large, longitudinal survey study of a nationally representative sample of adolescents in the United States. Lagged negative binomial and logistic regression and propensity score matching models (n = 2,250), fixed-effects models of within-individual change (n = 3,061), and random-effects models of sibling differences (n = 618) all showed that married men engaged in significantly less antisocial behavior than unmarried men. Our findings replicate results from other quasiexperimental studies of marriage and men's antisocial behavior and extend the results to a nationally representative sample of young adults in the United States.

scholarly journals Examining the Relationship between Household Vehicle Ownership and Ridesharing Behaviors in the United States

2018 ◽  
Vol 10 (8) ◽  
pp. 2720 ◽  
Author(s):  
Yuanyuan Zhang ◽  
Yuming Zhang
Keyword(s):  
United States ◽  
Population Density ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Cost Effective ◽  
The United States ◽  
Potential Effect ◽  
Transportation Systems ◽  
Transport Systems ◽  
Vehicle Ownership

To improve the sustainability and efficiency of transport systems, communities and government agencies throughout the United States (US) are looking for ways to reduce vehicle ownership and single-occupant trips by encouraging people to shift from driving to using more sustainable transport modes (such as ridesharing). Ridesharing is a cost-effective, sustainable and effective alternative transportation mode that is beneficial to the environment, the economy and society. Despite the potential effect of vehicle ownership on the adoption of ridesharing services, individuals’ ridesharing behaviors and the interdependencies between vehicle ownership and ridesharing usage are not well understood. This study aims to fill the gap by examining the associations between household vehicle ownership and the frequency and probability of ridesharing usage, and to estimate the effects of household vehicle ownership on individuals’ ridesharing usage in the US. We conducted zero-inflated negative binomial regression models using data from the 2017 National Household Travel Survey. The results show that, in general, one-vehicle reduction in households was significantly associated with a 7.9% increase in the frequency of ridesharing usage and a 23.0% increase in the probability of ridesharing usage. The effects of household vehicle ownership on the frequency of ridesharing usage are greater for those who live in areas with a higher population density than those living in areas with a lower population density. Young people, men, those who are unable to drive, individuals with high household income levels, and those who live in areas with rail service or a higher population density, tend to use ridesharing more frequently and are more likely to use it. These findings can be used as guides for planners or practitioners to better understand individuals’ ridesharing behaviors, and to identify policies and interventions to increase the potential of ridesharing usage, and to decrease household vehicle ownership, depending on different contextual features and demographic variables. Comprehensive strategies that limit vehicle ownership and address the increasing demand for ridesharing have the potential to improve the sustainability of transportation systems.

scholarly journals Statewide Interventions and Covid-19 Mortality in the United States: An Observational Study

2020 ◽  
Author(s):  
Nadir Yehya ◽  
Atheendar Venkataramani ◽  
Michael O Harhay
Keyword(s):  
United States ◽  
Negative Binomial ◽  
State Level ◽  
Negative Binomial Regression ◽  
The United States ◽  
School Closure ◽  
Sensitivity Analyses ◽  
Test Model ◽  
School Closures ◽  
Social Distancing

ABSTRACT Background Social distancing is encouraged to mitigate viral spreading during outbreaks. However, the association between distancing and patient-centered outcomes in Covid-19 has not been demonstrated. In the United States social distancing orders are implemented at the state level with variable timing of onset. Emergency declarations and school closures were two early statewide interventions. Methods To determine whether later distancing interventions were associated with higher mortality, we performed a state-level analysis in 55,146 Covid-19 non-survivors. We tested the association between timing of emergency declarations and school closures with 28-day mortality using multivariable negative binomial regression. Day 1 for each state was set to when they recorded ≥ 10 deaths. We performed sensitivity analyses to test model assumptions. Results At time of analysis, 37 of 50 states had ≥ 10 deaths and 28 follow-up days. Both later emergency declaration (adjusted mortality rate ratio [aMRR] 1.05 per day delay, 95% CI 1.00 to 1.09, p=0.040) and later school closure (aMRR 1.05, 95% CI 1.01 to 1.09, p=0.008) were associated with more deaths. When assessing all 50 states and setting day 1 to the day a state recorded its first death, delays in declaring an emergency (aMRR 1.05, 95% CI 1.01 to 1.09, p=0.020) or closing schools (aMRR 1.06, 95% CI 1.03 to 1.09, p<0.001) were associated with more deaths. Results were unchanged when excluding New York and New Jersey. Conclusions Later statewide emergency declarations and school closure were associated with higher Covid-19 mortality. Each day of delay increased mortality risk 5 to 6%.

Evolving epidemiology of reported cryptosporidiosis cases in the United States, 1995–2012

2015 ◽  
Vol 144 (8) ◽  
pp. 1792-1802 ◽  
Author(s):  
J. E. PAINTER ◽  
J. W. GARGANO ◽  
J. S. YODER ◽  
S. A. COLLIER ◽  
M. C. HLAVSA
Keyword(s):  
United States ◽  
Risk Factors ◽  
Race And Ethnicity ◽  
Negative Binomial ◽  
Disease Outbreaks ◽  
Negative Binomial Regression ◽  
The United States ◽  
Case Status ◽  
Estimate Rate ◽  
Rate Ratios

SUMMARYCryptosporidiumis the leading aetiology of waterborne disease outbreaks in the United States. This report briefly describes the temporal and geographical distribution of US cryptosporidiosis cases and presents analyses of cryptosporidiosis case data reported in the United States for 1995–2012. The Cochran–Armitage test was used to assess changes in the proportions of cases by case status (confirmedvs.non-confirmed), sex, race, and ethnicity over the study period. Negative binomial regression models were used to estimate rate ratios (RR) and 95% confidence intervals (CI) for comparing rates across three time periods (1995–2004, 2005–2008, 2009–2012). The proportion of confirmed cases significantly decreased (P< 0·0001), and a crossover from male to female predominance in case-patients occurred (P< 0·0001). Overall, compared to 1995–2004, rates were higher in 2005–2008 (RR 2·92, 95% CI 2·08–4·09) and 2009–2012 (RR 2·66, 95% CI 1·90–3·73). However, rate changes from 2005–2008 to 2009–2012 varied by age group (Pinteraction< 0·0001): 0–14 years (RR 0·55, 95% CI 0·42–0·71), 15–44 years (RR 0·99, 95% CI 0·82–1·19), 45–64 years (RR 1·47, 95% CI 1·21–1·79) and ⩾65 years (RR 2·18, 95% CI 1·46–3·25). The evolving epidemiology of cryptosporidiosis necessitates further identification of risk factors in population subgroups. Adding systematic molecular typing ofCryptosporidiumspecimens to US national cryptosporidiosis surveillance would help further identify risk factors and markedly expand understanding of cryptosporidiosis epidemiology in the United States.

Risk Analysis of Freight Train Collisions in the United States, 2000 to 2014

2016 ◽  
Author(s):  
Yanlei Wang ◽  
Shuang Xu ◽  
Xiang Liu
Keyword(s):  
United States ◽  
Risk Analysis ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
The United States ◽  
Rolling Stock ◽  
Environmental Damage ◽  
Collision Risk ◽  
Freight Train ◽  
Damage Costs

Train accidents damage infrastructure and rolling stock, disrupt operations, and may result in casualties and environmental damage. While the majority of previous studies focused on the safety risks associated with train derailments or highway-rail grade crossing collisions, much less work has been undertaken to evaluate train collision risk. This paper develops a statistical risk analysis methodology for freight-train collisions in the United States between 2000 and 2014. Negative binomial regression models are developed to estimate the frequency of freight-train collisions as a function of year and traffic volume by accident cause. Train collision severity, measured by the average number of railcars derailed, varied with accident cause. Train collision risk, defined as the product of collision frequency and severity, is predicted for 2015 to 2017, based on the 2000 to 2014 safety trend. The statistical procedures developed in this paper can be adapted to various other types of consequences, such as damage costs or casualties. Ultimately, this paper and its sequent studies aim to provide the railroad industry with data analytic tools to discover useful information from historical accidents so as to make risk-informed safety decisions.

scholarly journals Exploring the Relationship between Ridesharing and Public Transit Use in the United States

2018 ◽  
Vol 15 (8) ◽  
pp. 1763 ◽  
Author(s):  
Yuanyuan Zhang ◽  
Yuming Zhang
Keyword(s):  
United States ◽  
Negative Binomial ◽  
Public Transit ◽  
Negative Binomial Regression ◽  
Cost Effective ◽  
The United States ◽  
Sustainable Mobility ◽  
Environmentally Sustainable ◽  
Individual Level ◽  
Transit Use

Car travel accounts for the largest share of transportation-related greenhouse gas emissions in the United States (U.S.), leading to serious air pollution and negative health effects; approximately 76.3% of car trips are single-occupant. To reduce the negative externalities of cars, ridesharing and public transit are advocated as cost-effective and more environmentally sustainable alternatives. A better understanding of individuals’ uses of these two transport modes and their relationship is important for transport operators and policymakers; however, it is not well understood how ridesharing use is associated with public transit use. The objective of this study is to examine the relationships between the frequency and probability of ridesharing use and the frequency of public transit use in the U.S. Zero-inflated negative binomial regression models were employed to investigate the associations between these two modes, utilizing individual-level travel frequency data from the 2017 National Household Travel Survey. The survey data report the number of times the respondent had used ridesharing and public transit in the past 30 days. The results show that, generally, a one-unit increase in public transit use is significantly positively related to a 1.2% increase in the monthly frequency of ridesharing use and a 5.7% increase in the probability of ridesharing use. Additionally, the positive relationship between ridesharing and public transit use was more pronounced for people who live in areas with a high population density or in households with fewer vehicles. These findings highlight the potential for integrating public transit and ridesharing systems to provide easier multimodal transportation, promote the use of both modes, and enhance sustainable mobility, which are beneficial for the environment and public health.

Psychological distress among Bhutanese refugees living in the northeast region of the United States

2021 ◽  
Author(s):  
Ramraj Gautam ◽  
Jason Rydberg ◽  
Ivy Ho ◽  
Bhola Siwakoti ◽  
William Chadbourne ◽  
...  
Keyword(s):  
Mental Health ◽  
United States ◽  
Psychological Distress ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
The United States ◽  
Future Research ◽  
Related Factors ◽  
Bhutanese Refugees ◽  
The Impact

Abstract The purpose of this study was to examine predictors of psychological distress among adult Bhutanese refugees living in the United States. We recruited 376 adult Bhutanese refugees living in the northeast US region, the majority of whom were employed, married men in their 40 s who were US citizens. Using Bayesian Negative Binomial Regression modelling, we examined the impact of sociodemographic measures, health status and refugee integration measures on psychological distress outcomes. The most common predictors of depression, stress and anxiety were social connection deficits and self-reported health conditions. Other associated factors included: health access deficits, number of years living in the US, paid employment, citizenship and living in more than one US city. The findings of our study revealed that mental health outcomes in this subset of the population of Bhutanese refugees are impacted by a variety of social and health related factors. Public policy makers and practitioners need to recognize the complex issues affecting mental health of Bhutanese refugees. Advocacy for expanded culturally congruent policies and evidence based mental health services are recommended. Future research needs to examine culturally relevant concepts and measures related to mental health and integration in this population.

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