Event Count Models Research Articles

Does Youth Resentment Matter in Understanding the Surge of Extremist Violence in Burkina Faso?

Abstract The year 2019 marked an unprecedented step in violence in Burkina Faso. Before 2018, attacks targeted central government officials and expatriates. In 2019, the victims of sexual assaults, attacks, abductions or forced disappearances and assassinations were mostly local civilians. The surge in these violent attacks against civilians generates population movements. As of 2023, internally displaced people represent about 10% of the total population in the country. Several observers point to the youth of the attackers. This study investigates the motives that could drive young people to resort to violence in the country. It aims to highlight youth resentment's effect on violence against civilians in the country as of 2019. It takes advantage of one of the latest nationwide United Nations Children’s Fund (UNICEF)-sponsored surveys conducted in Burkina Faso before some parts of the country became inaccessible because of attacks. Among other information, this survey collected data on youth resentment towards the ability of their kinship to fulfil their needs in 2018, namely before the shift in violence against civilians. We merge this survey into an original dataset that gathers data from the Armed Conflict Location and Event Data Project (ACLED), mining data from the MINEX project and distance data computed using Burkina Faso's roads information. The results of an event count model show that youth resentment matters in understanding the occurrence of conflicts. Moreover, the presence of mining companies, the remoteness of infrastructures, ethnic diversity and polarisation also significantly affect violence against civilians.

Evaluating Bayesian Radiocarbon‐dated Event Count (REC) models for the study of long‐term human and environmental processes

ABSTRACTChronological uncertainty complicates attempts to use radiocarbon dates as proxies for processes such as human population growth/decline, forest fires and marine ingression. Established approaches involve turning databases of radiocarbon‐date densities into single summary proxies that cannot fully account for chronological uncertainty. Here, I use simulated data to explore an alternative Bayesian approach that instead models the data as what they are, namely radiocarbon‐dated event counts. The approach involves assessing possible event‐count sequences by sampling radiocarbon date densities and then applying a Markov Chain Monte Carlo method to estimate the parameters of an appropriate count‐based regression model. The regressions based on individual sampled sequences were placed in a multilevel framework, which allowed for the estimation of hyperparameters that account for chronological uncertainty in individual event times. Two processes were used to produce simulated data. One represented a simple monotonic change in event‐counts and the other was based on a real palaeoclimate proxy record. In both cases, the method produced estimates that had the correct sign and were consistently biased towards zero. These results indicate that the approach is widely applicable and could form the basis of a new class of quantitative models for use in exploring long‐term human and environmental processes.

Gendered Polarization and Abortion Policymaking in the States

Abstract Widening, asymmetric polarization is evident in both the U.S. Congress and state legislatures. Recent work unveils a new dimension to this polarization story: newly elected Republican women are driving this polarization. Women are more likely to legislate on women’s issues than men, yet women’s shared interest in representing women doesn’t preclude their identity as partisans. In this article, we explore the effect of today’s political climate on state legislators’ policy representation of women’s issues. We ask what effect does gendered polarization have on women’s issues? To test this, we evaluate bill sponsorship in the states on the quintessential “women’s issue” of abortion. Our research design focuses on bill introductions and uses on an original dataset of pro- and anti-abortion rights bill introductions, which we analyze using an event count model. We find that overall polarization leads to the introduction of fewer restrictive abortion bills, but as polarization between women lawmakers grows, legislators are more likely to introduce anti-abortion rights legislation. Gender polarization has consequences on the types of bills legislators introduce and for how scholars should study polarization.

Analysis of the Characteristics and Number of Bicycle–Passenger Conflicts at Bus Stops for Improving Safety

This study aimed to analyze the characteristics of bicycle–passenger conflicts at bus stops and develop a model to predict the number of conflicts accurately. This paper investigated the traffic flow operation at bus stops by video recording. Duration and distribution characteristics of bicycle–passenger conflicts were statistically analyzed. Then four types of conflicts defined based on evasive behavior (cyclist yielding as Type 1, cyclist bypassing as Type 2, passenger yielding as Type 3, and passenger bypassing as Type 4) were compared. A generalized event count (GEC) model was established for bicycle–passenger conflict estimation and analysis. The main results indicated that: (1) The average conflict duration was 1.716 s, whilst 60.9% of conflicts existed near the accesses of bus stops in longitudinal direction; (2) Type 1 conflict was significantly different from Type 2, 3, and 4 conflicts in duration, whilst the three had no significant difference; (3) the proposed GEC model showed good performance in predicting bicycle–passenger conflicts, with 15.71% of mean-absolute-percentage-error and 0.8772 of R2; and (4) bicycle volume, bus passenger volume, and passenger crossing time were critical factors impacting the number of bicycle–passenger conflicts. Finally, transport agencies may consider installing separations and crosswalks to improve the safety of the stop area.

Crash data modeling with a generalized estimator

The investigation of relationships between traffic crashes and relevant factors is important in traffic safety management. Various methods have been developed for modeling crash data. In real world scenarios, crash data often display the characteristics of over-dispersion. However, on occasions, some crash datasets have exhibited under-dispersion, especially in cases where the data are conditioned upon the mean. The commonly used models (such as the Poisson and the NB regression models) have associated limitations to cope with various degrees of dispersion. In light of this, a generalized event count (GEC) model, which can be generally used to handle over-, equi-, and under-dispersed data, is proposed in this study.This model was first applied to case studies using data from Toronto, characterized by over-dispersion, and then to crash data from railway-highway crossings in Korea, characterized with under-dispersion. The results from the GEC model were compared with those from the Negative binomial and the hyper-Poisson models. The cases studies show that the proposed model provides good performance for crash data characterized with over- and under-dispersion. Moreover, the proposed model simplifies the modeling process and the prediction of crash data.

Making Washington Work: Legislative Entrepreneurship and the Personal Vote from the Gilded Age to the Great Depression

AbstractStudies of bill sponsorship in the modern Congress highlight the effects of constituency characteristics, seniority, and committee membership. These studies, however, are limited in their ability to assess the effects of institutions. We provide the first systematic study of bill sponsorship in the premodern House of Representatives. In doing so, we take advantage of this period's expansive legislative agenda and variation in electoral system rules. Using matching and event count models, we estimate the effects of institutions, electoral competition, and members’ institutional positions and political experiences on their sponsorship of different types of bills. We find that two reforms—the Australian ballot and nominating primary—increased sponsorship of bills designed to cultivate personal votes, thereby contributing to the growth in private legislation and bills aimed at local constituencies. Our results establish these reforms as a major event shaping lawmaking activity and, with it, the character of contemporary representation.

Modeling Urinary Dysfunction After External Beam Radiation Therapy of the Prostate Using Bladder Dose-Surface Maps: Evidence of Spatially Variable Response of the Bladder Surface

We assessed the association of the spatial distribution of dose to the bladder surface, described using dose-surface maps, with the risk of urinary dysfunction. The bladder dose-surface maps of 754 participants from the TROG 03.04-RADAR trial were generated from the volumetric data by virtually cutting the bladder at the sagittal slice, intersecting the bladder center-of-mass through to the bladder posterior and projecting the dose information on a 2-dimensional plane. Pixelwise dose comparisons were performed between patients with and without symptoms (dysuria, hematuria, incontinence, and an International Prostate Symptom Score increase of ≥10 [ΔIPSS10]). The results with and without permutation-based multiple-comparison adjustments are reported. The pixelwise multivariate analysis findings (peak-event model for dysuria, hematuria, and ΔIPSS10; event-count model for incontinence), with adjustments for clinical factors, are also reported. The associations of the spatially specific dose measures to urinary dysfunction were dependent on the presence of specific symptoms. The doses received by the anteroinferior and, to lesser extent, posterosuperior surface of the bladder had the strongest relationship with the incidence of dysuria, hematuria, and ΔIPSS10, both with and without adjustment for clinical factors. For the doses to the posteroinferior region corresponding to the area of the trigone, the only symptom with significance was incontinence. A spatially variable response of the bladder surface to the dose was found for symptoms of urinary dysfunction. Limiting the dose extending anteriorly might help reduce the risk of urinary dysfunction.

An analysis of spatial correlates of terrorism using risk terrain modeling

ABSTRACTThe purpose of this study is to identify correlates of terrorism in space. It examines whether places with terrorist incidents show similar patterns with respect to the physical features across landscape, and tests the spatial influence of various features of environment on the incidence of terrorism. Drawing on the locations of violent terrorist offenses committed between 2008 and 2012, the study in Istanbul applies the Risk Terrain Modeling framework to terrorism. It uses data on police incidents and infrastructure (e.g., government buildings or parks). The analysis employs GIS techniques and an event count model, and combines all risky layers in a composite map to understand where the risk is higher. The study suggests a concentration of 1153 violent terrorist incidents relative to key physical factors by identifying seventeen potential risk factors, eight of which were significantly correlated in the model. Regardless of terrorists’ intent, the significantly associated establishments increase the risk in the surrounding areas where these features are located. The coexistence of leisure places such as bakeries, religious facilities, or eateries results in higher risks. While the environmental backcloth may constitute a risk for terrorism, its components may also help forecast the locations of terrorist incidents in the future.

The Deterrent Effects of the International Criminal Court: Evidence from Libya

ABSTRACTThe International Criminal Court (ICC) was designed to try the worst war criminals for crimes against humanity, genocide, and other instances of mass human suffering. By providing a permanent, international mechanism to hold perpetrators of mass human rights abuse accountable, the ICC is also meant to be a deterrent—to prevent potential genocidaires from committing systematic human rights abuses in the first place. But what if the effect is actually quite the opposite? While advocates of international justice have made conjectures about the effect of the ICC on stopping human rights abuses, the existing scholarship does not empirically test assumptions about the relationship between international criminal justice and violence. This article outlines the causal mechanisms by which the ICC could affect ongoing violence and tests these assumptions using event count models of the relationship between the ICC and the level of violence against civilians in Libya during the 2011 crisis. These analyses suggest that the ICC’s involvement in conflict does have a dampening effect on the level of mass atrocities committed. The results also call for a broad and sustained research agenda on the effect of international accountability efforts on ongoing violence.

Urinary symptoms following external beam radiotherapy of the prostate: Dose–symptom correlates with multiple-event and event-count models

Background and purposeThis study aimed to compare urinary dose–symptom correlates after external beam radiotherapy of the prostate using commonly utilised peak-symptom models to multiple-event and event-count models which account for repeated events. Materials and methodsUrinary symptoms (dysuria, haematuria, incontinence and frequency) from 754 participants from TROG 03.04-RADAR trial were analysed. Relative (R1–R75Gy) and absolute (A60–A75Gy) bladder dose-surface area receiving more than a threshold dose and equivalent uniform dose using exponent a (range: a∈[1 … 100]) were derived. The dose–symptom correlates were analysed using; peak-symptom (logistic), multiple-event (generalised estimating equation) and event-count (negative binomial regression) models. ResultsStronger dose–symptom correlates were found for incontinence and frequency using multiple-event and/or event-count models. For dysuria and haematuria, similar or better relationships were found using peak-symptom models. Dysuria, haematuria and high grade (⩾2) incontinence were associated to high dose (R61–R71Gy). Frequency and low grade (⩾1) incontinence were associated to low and intermediate dose-surface parameters (R13–R41Gy). Frequency showed a parallel behaviour (a=1) while dysuria, haematuria and incontinence showed a more serial behaviour (a=4 to a⩾100). Relative dose-surface showed stronger dose–symptom associations. ConclusionsFor certain endpoints, the multiple-event and event-count models provide stronger correlates over peak-symptom models. Accounting for multiple events may be advantageous for a more complete understanding of urinary dose–symptom relationships.

Testing for Zero Inflation in Count Models: Bias Correction for the Vuong Test

The proportion of zeros in event-count processes may be inflated by an additional mechanism by which zeros are created. This has given rise to statistical models that accommodate zero inflation; these are available in Stata through the zip and zinb commands. The Vuong (1989, Econometrica 57: 307–333) test is regularly used to determine whether estimating a zero-inflation component is appropriate or whether a single-equation count model should be used. The use of the Vuong test in this case is complicated by the fact that zero-inflated models involve the estimation of several more parameters than the single-equation models. Although Vuong (1989, Econometrica 57: 307–333) suggested corrections to the test statistic to address the comparison of models with different numbers of parameters, Stata does not implement any such correction. The result is that the Vuong test used by Stata is biased toward supporting the model with a zero-inflation component, even when no zero inflation exists in the generative process. We provide new Stata commands for computing the Vuong statistic with corrections based on the Akaike and Bayesian (Schwarz) information criteria. In an extensive Monte Carlo study, we illustrate the bias inherent in using the uncorrected Vuong test, and we examine the relative merits of the Akaike and Schwarz corrections. Then, in an empirical example from international relations research, we show that errors in selecting an event-count model can have clear implications for substantive conclusions.

Weather, terrain and warfare: Coalition fatalities in Afghanistan

The study of conflict increasingly focuses on events and relationships within wars. Among these is the relationship between physical geography and violence. Careful examinations of the relationship between physical geography, especially weather, and events within wars are, however, still few. With increasingly available data on the violence within wars and the physical geography within states, the opportunities for such quantitative analysis have grown. In particular, the ongoing war in Afghanistan provides a useful opportunity to examine this relationship. Using this conflict, we test an argument about how the constraints and opportunities provided by physical geography, in particular daily and seasonal measures of weather, explain combat fatalities. We evaluate our argument with a series of event count models and find consistently significant evidence connecting warm temperatures, decreased visibility and windy conditions to coalition combat fatalities. Alternatively, we find mixed support that the more commonly studied elements of physical geography, distance and rough terrain are connected to these fatalities.

Modeling 802.11 AP usage through daily keep-alive event counts

Wireless and in particular 802.11 is one of the major technologies for accessing the Internet at home, in coffee shops, enterprises, university campuses, and other public places. While most recent works on modeling wireless sites focuses on user mobility and user residing time, this paper presents and compares a number of models for characterizing access point (AP) usage including time-dependent models that considers week structure usage. Moreover, rather than looking at throughput we focus on daily counts of keep-alive events that mobile devices generate every 15 min while they are connected to the wireless network. We model both daily event counts and above---below AP event counts average binary indicator. Our models are trained and evaluated on data collected from Porto hotspot of Eduroam, the European academic wireless network. The models we present are generative, in the sense they can be used to generate synthetic daily event counts for a single AP or a collection of APs. We provide standard cross-validation comparison of models using the log-likelihood of the models on training and test data. We conclude that significant improvements in AP usage modeling capability can be observed by considering (1) simple time dependency (2) week-days/week-ends usage structure and (3) individual day's usage; whereas extending the complexity of time dependency ordering of AP's usage samples does not show significant improvements for daily event count models.

Poverty, social disadvantage, and the black/white placement gap

Abstract In this paper, we examine whether county-level measures of poverty and social disadvantage are correlated with county-level variation in the black/white foster care placement gap. The black/white placement gap refers to the fact that when the rate of placement into foster care for black children is compared to the rate for white children living in the same area, the black placement rate is almost always higher than the rate for whites. Although differential exposure to poverty is often used to explain why the placement gap is so large, the problem has rarely been studied. Using Poisson event count models, we find that poverty, measured at the county ecological level, is associated with a narrower gap rather than a wider gap. The counterintuitive finding is due to the fact that the relationship between poverty and placement rates depends on race.

Blurring Borders: The Effect of Federal Activism on Interstate Cooperation

Interstate compacts are an increasingly important policy tool available to states, one that allows them to tackle regional and national issues. What effect does policy activity at the federal level have on state participation in interstate compacts? Drawing on theories of functional federalism, the authors explore the possibility that a state’s response to federal activism varies across policy domains. For economic policy the authors hypothesize that federal activism causes an increase in compact participation, as states attempt to defend themselves against federal intrusion. In other policy areas the authors expect that states are more likely to enter into compacts during periods of relative federal inactivity. Results from a set of event-count models generally support these hypotheses. The study findings suggest that states may sometimes use interstate compacts as a mechanism to resist federal incursion but that this is just one facet of a more complex pattern of intergovernmental policy adjustment.

Increased risk of infectious disease requiring hospitalization among patients with psoriasis: A population-based cohort

Immunologic alterations caused by psoriasis and/or its therapies may affect the risk of serious infections. For patients with psoriasis, we explored the overall and therapy-related risk of contracting an infectious disease (ID) requiring hospitalization in a large population-based cohort. The incidence of ID was compared between patients with psoriasis and a randomly selected cohort (ratio 1:5) using hospital and pharmacy databases covering 2.5 million Dutch residents between 1997 and 2008. First and multiple IDs were defined and categorized into 20 groups based on primary International Classification of Diseases, Ninth Revision, Clinical Modification discharge diagnoses. Multivariate Cox regression and Poisson event-count models were used to test the risk difference of IDs between patients with psoriasis and reference cohort. A total of 25,742 patients with psoriasis and 128,710 reference subjects were followed up for approximately 6 years. The likelihood of IDs in patients with psoriasis was twice as high as the reference population (908 vs 438 events/100,000 person-years, crude hazard ratio 2.08, 95% confidence interval 1.96-2.22). In a multivariate model the hazard ratio decreased to 1.54 (95% confidence interval 1.44-1.65). This risk was highest for patients with more severe psoriasis (adjusted hazard ratio 1.81, 95% confidence interval 1.57-2.08), but was not associated with recent systemic antipsoriatic drug dispensing. Respiratory tract, abdominal, and skin infections occurred most frequently in patients with psoriasis. Multiple event analysis that counted the total number of infectious discharge diagnoses gave similar results. No data were available on lifestyle factors. The risk of severe infections was significantly higher for patients with psoriasis compared with control subjects and could not be explained by exposure to systemic antipsoriatic drugs.

Expanding the Scope of Conflict: Interest Groups and Interstate Compacts*

Objective. This study looks at how the characteristics of states' interest group environments affect state participation in interstate compacts. Drawing on prominent theories of interest system characteristics, we hypothesize that interest group density and concentration will influence a state's propensity to join compacts. Method. Using pooled cross-sectional time-series event-count models, we test our hypotheses for 48 states over a 30-year period. Results. We find that states with denser interest group systems are more likely to join interstate compacts, but that greater concentration of organized interests in a few economic sectors impedes compact formation. Additional analyses show that the effects of state interest group systems vary across types of interest groups and compacts. In particular, the effects of interest group density appear to be driven primarily by not-for-profit groups generating increased state participation in noneconomic compacts. Conclusion. Interstate cooperation is influenced in important ways by characteristics of interest group environments.

Sliding Doors of Opportunity: Zapatistas and Their Cycle of Protest

Using a cross-sectional time-series event-count model, this study analyzes the effects of local, national, and international variables on pro-Zapatista protests across the 111 localities (municipios) of Chiapas over a ten-year period (1994-2003). Protests were more likely to occur in localities with previous protest activity, a closed political system, and a larger presence of the military. Local and national electoral openings, as well as a larger local and national presence of the Zapatistas' presumed political ally, the Partido de la Revolución Democrática (PRD), had a negative relationship with protest activity. Specific openings to the Zapatistas also worked as protest depressants. International attention did not show any significant effect on Zapatista protest activity. However, these institutional and specific openings were only ephemeral opportunities in that they did not translate into substantive concessions for the movement. They appear to have decreased the strength of the Zapatista protest cycle, while the international attention to the movement did not show any significant effect on it.

Approaches to Modeling the Adoption and Diffusion of Policies with Multiple Components

AbstractScholars have begun to move beyond the dichotomous dependent variable—indicating whether a state adopts a policy or not in a given year—usually employed in event history analysis. In particular, they have devoted increasing attention to the components of policies that states adopt. I discuss a variety of estimators that have been employed to analyze the adoption and modification of policies with multiple components, including various forms of event history analysis, OLS, and event count models. With various modifications, the researcher can estimate models that treat each component as distinct, pool these models to leverage commonalities across components, or treat the components as identical parts of the same process. Each of these has its strengths and may be appropriate in certain circumstances. Nonetheless, in the majority of cases, some version of event history analysis for multiple or repeat failures is likely to be preferred. The different approaches are illustrated by studying state adoption of various obesity-related policies.

Explaining Major and Third Party Candidate Entry in U.S. Gubernatorial Elections, 1980–2005

AbstractWhile much scholarly research has focused on the quality of candidates in U.S. elections, the quantity of candidate participation has received much less attention. Consequently, there is little systematic evidence on what factors stimulate or dampen candidate entry into electoral contests, especially at the state level. In this article, we examine the effects of electoral laws, states' social and political climates, and incumbency on gubernatorial candidacies. We test our claims using an event-count model with the number of candidates contesting each gubernatorial election from 1980 to 2005 as the outcome of interest. We divide total candidate participation into major and third party candidates to observe whether the factors affect neither, one, or both types of candidacies. We find that electoral laws and incumbency play an important role in determining the number of candidacies in these elections, but the effect of these factors varies for the two types of candidates.