scholarly journals A Longitudinal Analysis of the Impact of Distance Driven on the Probability of Car Accidents

Risks ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 91
Author(s):  
Jean-Philippe Boucher ◽  
Roxane Turcotte

Using telematics data, we study the relationship between claim frequency and distance driven through different models by observing smooth functions. We used Generalized Additive Models (GAM) for a Poisson distribution, and Generalized Additive Models for Location, Scale, and Shape (GAMLSS) that we generalize for panel count data. To correctly observe the relationship between distance driven and claim frequency, we show that a Poisson distribution with fixed effects should be used because it removes residual heterogeneity that was incorrectly captured by previous models based on GAM and GAMLSS theory. We show that an approximately linear relationship between distance driven and claim frequency can be derived. We argue that this approach can be used to compute the premium surcharge for additional kilometers the insured wants to drive, or as the basis to construct Pay-as-you-drive (PAYD) insurance for self-service vehicles. All models are illustrated using data from a major Canadian insurance company.

Author(s):  
Mark David Walker ◽  
Mihály Sulyok

Abstract Background Restrictions on social interaction and movement were implemented by the German government in March 2020 to reduce the transmission of coronavirus disease 2019 (COVID-19). Apple's “Mobility Trends” (AMT) data details levels of community mobility; it is a novel resource of potential use to epidemiologists. Objective The aim of the study is to use AMT data to examine the relationship between mobility and COVID-19 case occurrence for Germany. Is a change in mobility apparent following COVID-19 and the implementation of social restrictions? Is there a relationship between mobility and COVID-19 occurrence in Germany? Methods AMT data illustrates mobility levels throughout the epidemic, allowing the relationship between mobility and disease to be examined. Generalized additive models (GAMs) were established for Germany, with mobility categories, and date, as explanatory variables, and case numbers as response. Results Clear reductions in mobility occurred following the implementation of movement restrictions. There was a negative correlation between mobility and confirmed case numbers. GAM using all three categories of mobility data accounted for case occurrence as well and was favorable (AIC or Akaike Information Criterion: 2504) to models using categories separately (AIC with “driving,” 2511. “transit,” 2513. “walking,” 2508). Conclusion These results suggest an association between mobility and case occurrence. Further examination of the relationship between movement restrictions and COVID-19 transmission may be pertinent. The study shows how new sources of online data can be used to investigate problems in epidemiology.


Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 299
Author(s):  
Jaime Pinilla ◽  
Miguel Negrín

The interrupted time series analysis is a quasi-experimental design used to evaluate the effectiveness of an intervention. Segmented linear regression models have been the most used models to carry out this analysis. However, they assume a linear trend that may not be appropriate in many situations. In this paper, we show how generalized additive models (GAMs), a non-parametric regression-based method, can be useful to accommodate nonlinear trends. An analysis with simulated data is carried out to assess the performance of both models. Data were simulated from linear and non-linear (quadratic and cubic) functions. The results of this analysis show how GAMs improve on segmented linear regression models when the trend is non-linear, but they also show a good performance when the trend is linear. A real-life application where the impact of the 2012 Spanish cost-sharing reforms on pharmaceutical prescription is also analyzed. Seasonality and an indicator variable for the stockpiling effect are included as explanatory variables. The segmented linear regression model shows good fit of the data. However, the GAM concludes that the hypothesis of linear trend is rejected. The estimated level shift is similar for both models but the cumulative absolute effect on the number of prescriptions is lower in GAM.


2021 ◽  
pp. 1-10
Author(s):  
Hanna M. van Loo ◽  
Lian Beijers ◽  
Martijn Wieling ◽  
Trynke R. de Jong ◽  
Robert A. Schoevers ◽  
...  

Abstract Background Most epidemiological studies show a decrease of internalizing disorders at older ages, but it is unclear how the prevalence exactly changes with age, and whether there are different patterns for internalizing symptoms and traits, and for men and women. This study investigates the impact of age and sex on the point prevalence across different mood and anxiety disorders, internalizing symptoms, and neuroticism. Methods We used cross-sectional data on 146 315 subjects, aged 18–80 years, from the Lifelines Cohort Study, a Dutch general population sample. Between 2012 and 2016, five current internalizing disorders – major depression, dysthymia, generalized anxiety disorder, social phobia, and panic disorder – were assessed according to DSM-IV criteria. Depressive symptoms, anxiety symptoms, neuroticism, and negative affect (NA) were also measured. Generalized additive models were used to identify nonlinear patterns across age, and to investigate sex differences. Results The point prevalence of internalizing disorders generally increased between the ages of 18 and 30 years, stabilized between 30 and 50, and decreased after age 50. The patterns of internalizing symptoms and traits were different. NA and neuroticism gradually decreased after age 18. Women reported more internalizing disorders than men, but the relative difference remained stable across age (relative risk ~1.7). Conclusions The point prevalence of internalizing disorders was typically highest between age 30 and 50, but there were differences between the disorders, which could indicate differences in etiology. The relative gap between the sexes remained similar across age, suggesting that changes in sex hormones around the menopause do not significantly influence women's risk of internalizing disorders.


Author(s):  
Marcos Samuel Matias Ribeiro ◽  
Lara de Melo Barbosa Andrade ◽  
Maria Helena Constantino Spyrides ◽  
Kellen Carla Lima ◽  
Pollyane Evangelista da Silva ◽  
...  

AbstractThe occurrence of environmental disasters affects different social segments, impacting health, education, housing, economy and the provision of basic services. Thus, the objective of this study was to estimate the relationship between the occurrence of disasters and extreme climate, sociosanitary and demographic conditions in the Northeast region of Brazil during the period from 1993 to 2013. Initially, we analyzed the spatial pattern of the incidence of events and, subsequently, generalized additive models for location, scale and shape were used in order to identify and estimate the magnitude of associations between factors. Results showed that droughts are the predominant disasters in the NEB representing 81.1% of the cases, followed by events triggered by excessive rainfall such as flash floods (11.1%) and floods (7.8%). Climate conditions presented statistically significant associations with the analyzed disasters, in which indicators of excess rainfall positively contributed to the occurrence of flash floods and floods, but negatively contributed to the occurrence of drought. Sociosanitary factors, such as percentage of households with inadequate sewage, waste collection and water supply, were also positively associated with the model’s estimations, i.e., contributing to an increase in the occurrence of events, with the exception of floods, which were not significantly influenced by sociosanitary parameters. A decrease of 19% in the risk of drought occurrence was estimated, on average. On the other hand, events caused by excessive rainfall increased by 40% and 57%, in the cases of flash floods and floods, respectively.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahdi Salehi ◽  
Safoura Rouhi ◽  
Mohana Usefi Moghadam ◽  
Faezeh Faramarzi

PurposeSuccess in corporate relative performance is one of the factors for the growth and durability of firms. Since the relative performance is a function of managers' decisions and such decisions are under the influence of behavioral and psychological characteristics, this paper aims to assess the managers’ and auditors’ narcissism's effect on the management team's stability relative to corporate performance.Design/methodology/approachThis paper has used the signature magnitude for examining narcissism and the regression model of Jenter and Kanaan (2015) for assessing relative corporate performance. The logistic regression is used to test the model of the management team's stability, and the multivariate regression is used to test the model of relative corporate performance. Research hypotheses were also examined using a sample of 768 listed year-companies on the Tehran Stock Exchange during 2012–2017 and by employing a panel data approach and fixed effects method.FindingsThe obtained results show a negative and significant relationship between managers' and auditors' narcissism and the management team's stability. The relationship between the narcissism of managers and auditors and relative corporate performance is positive and significant. Moreover, managers' narcissism positively and significantly impacts the relationship between auditors' narcissism and team management stability. A negative and significant relationship is evident between auditors’ narcissism and relative corporate performance.Originality/valueThis study's results can identify the effect of psychological components such as narcissism on people's performance by directing and influencing their decisions. Many studies have been conducted on narcissism, but none of them have examined the impact auditors’ and managers' narcissism has on the management team's stability and the corporate relative performance. Therefore, considering the importance of success in the corporate relative performance and benefits of the management team's stability, this study's results can reveal the importance of such features in accounting research. Also, the results of this research can make it important to know more about financial behavioral theory.


Author(s):  
R. Tamara Konetzka ◽  
Hari Sharma ◽  
Jeongyoung Park

An ongoing concern about medical malpractice litigation is that it may induce provider exit, potentially affecting consumer welfare. The nursing home sector is subject to substantial litigation activity but remains generally understudied in terms of the effects of litigation, due perhaps to a paucity of readily available data. In this article, we estimate the association between litigation and nursing home exit (closure or change in ownership), separating the impact of malpractice environment from direct litigation. We use 2 main data sources for this study: Westlaw’s Adverse Filings database (1997-2005) and Online Survey, Certification and Reporting data sets (1997-2005). We use probit models with state and year fixed effects to examine the relationship between litigation and the probability of nursing home closure or change in ownership with and without adjustment for malpractice environment. We examine the relationship on average and also stratify by profit status, chain membership, and market competition. We find that direct litigation against a nursing home has a nonsignificant effect on the probability of closure or change in ownership within the subsequent 2 years. In contrast, the broader malpractice environment has a significant effect on change in ownership, even for nursing homes that have not been sued, but not on closure. Effects are stronger among for-profit and chain facilities and those in more competitive markets. A high-risk malpractice environment is associated with change of ownership of nursing homes regardless of whether they have been directly sued, indicating that it is too blunt an instrument for weeding out low-quality nursing homes.


2021 ◽  
Vol 251 ◽  
pp. 01102
Author(s):  
Weiwei Fu ◽  
Peifen Zhuang

This paper collects the data of China’s aquatic products from 2002 to 2018 and studies the relationship between the production agglomeration and export competitiveness of aquatic products. This paper calculates the production Concentration Rate (CR) which reflects the degree of agglomeration of aquatic products and the Revealed Comparative Advantage (RCA) index which reflects the export competitiveness of aquatic products, and then uses variable intercept model with fixed effects to empirically analyze the impact of production agglomeration of three main aquatic products (fish, crustacean and shellfish) on the export competitiveness. The results show that there is an obvious phenomenon of production agglomeration of aquatic products in China. Overall, the improvement of production agglomeration of aquatic products is conducive to the promotion of export competitiveness.


2021 ◽  
Vol 2 (Supplement_1) ◽  
pp. A45-A45
Author(s):  
J Leota ◽  
D Hoffman ◽  
L Mascaro ◽  
M Czeisler ◽  
K Nash ◽  
...  

Abstract Introduction Home court advantage (HCA) in the National Basketball Association (NBA) is well-documented, yet the co-occurring drivers responsible for this advantage have proven difficult to examine in isolation. The Coronavirus disease (COVID-19) pandemic resulted in the elimination of crowds in ~50% of games during the 2020/2021 NBA season, whereas travel remained unchanged. Using this ‘natural experiment’, we investigated the impact of crowds and travel-related sleep and circadian disruption on NBA HCA. Methods 1080 games from the 2020/2021 NBA regular season were analyzed using mixed models (fixed effects: crowds, travel; random effects: team, opponent). Results In games with crowds, home teams won 58.65% of the time and outrebounded (M=2.28) and outscored (M=2.18) their opponents. In games without crowds, home teams won significantly less (50.60%, p = .01) and were outrebounded (M=-0.41, p < .001) and outscored (M=-0.13, p < .05) by their opponents. Further, the increase in home rebound margin fully mediated the relationship between crowds and home points margin (p < .001). No significant sleep or circadian effects were observed. Discussion Taken together, these results suggest that HCA in the 2020/2021 NBA season was predominately driven by the presence of crowds and their influence on the effort exerted by the home team to rebound the ball. Moreover, we speculate that the strict NBA COVID-19 policies may have mitigated the travel-related sleep and circadian effects on the road team. These findings are of considerable significance to a domain wherein marginal gains can have immense competitive, financial, and even historical consequences.


2021 ◽  
Author(s):  
Judith Neve ◽  
Guillaume A Rousselet

Sharing data has many benefits. However, data sharing rates remain low, for the most part well below 50%. A variety of interventions encouraging data sharing have been proposed. We focus here on editorial policies. Kidwell et al. (2016) assessed the impact of the introduction of badges in Psychological Science; Hardwicke et al. (2018) assessed the impact of Cognition’s mandatory data sharing policy. Both studies found policies to improve data sharing practices, but only assessed the impact of the policy for up to 25 months after its implementation. We examined the effect of these policies over a longer term by reusing their data and collecting a follow-up sample including articles published up until December 31st, 2019. We fit generalized additive models as these allow for a flexible assessment of the effect of time, in particular to identify non-linear changes in the trend. These models were compared to generalized linear models to examine whether the non-linearity is needed. Descriptive results and the outputs from generalized additive and linear models were coherent with previous findings: following the policies in Cognition and Psychological Science, data sharing statement rates increased immediately and continued to increase beyond the timeframes examined previously, until reaching close to 100%. In Clinical Psychological Science, data sharing statement rates started to increase only two years following the implementation of badges. Reusability rates jumped from close to 0% to around 50% but did not show changes within the pre-policy nor the post-policy timeframes. Journals that did not implement a policy showed no change in data sharing rates or reusability over time. There was variability across journals in the levels of increase, so we suggest future research should examine a larger number of policies to draw conclusions about their efficacy. We also encourage future research to investigate the barriers to data sharing specific to psychology subfields to identify the best interventions to tackle them.


2011 ◽  
Vol 68 (10) ◽  
pp. 2252-2263 ◽  
Author(s):  
Stéphanie Mahévas ◽  
Youen Vermard ◽  
Trevor Hutton ◽  
Ane Iriondo ◽  
Angélique Jadaud ◽  
...  

Abstract Mahévas, S., Vermard, Y., Hutton, T., Iriondo, A., Jadaud, A., Maravelias, C. D., Punzón, A., Sacchi, J., Tidd, A., Tsitsika, E., Marchal, P., Goascoz, N., Mortreux, S., and Roos, D. 2011. An investigation of human vs. technology-induced variation in catchability for a selection of European fishing fleets. – ICES Journal of Marine Science, 68: 2252–2263. The impact of the fishing effort exerted by a vessel on a population depends on catchability, which depends on population accessibility and fishing power. The work investigated whether the variation in fishing power could be the result of the technical characteristics of a vessel and/or its gear or whether it is a reflection of inter-vessel differences not accounted for by the technical attributes. These inter-vessel differences could be indicative of a skipper/crew experience effect. To improve understanding of the relationships, landings per unit effort (lpue) from logbooks and technical information on vessels and gears (collected during interviews) were used to identify variables that explained variations in fishing power. The analysis was undertaken by applying a combination of generalized additive models and generalized linear models to data from several European fleets. The study highlights the fact that taking into account information that is not routinely collected, e.g. length of headline, weight of otter boards, or type of groundrope, will significantly improve the modelled relationships between lpue and the variables that measure relative fishing power. The magnitude of the skipper/crew experience effect was weaker than the technical effect of the vessel and/or its gear.


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