Classification of territory risk by generalized linear and generalized linear mixed models

Territory risk analysis has played an important role in the decision-making of auto insurance rate regulation.Due to the optimality of insurance loss data groupings,clustering methods become the natural choice for such territory risk classification.In this work,spatially constrained clustering is first applied to insurance loss data to form rating territories.The generalized linear model(GLM)and generalized linear mixed model(GLMM)are then proposed to derive the risk relativities of obtained clusters.Each basic rating unit within the same cluster,namely Forward Sortation Area(FSA),takes the same risk relativity value as its cluster.The obtained risk relativities from GLM or GLMM are used to calculate the performance metrics,including RMSE,MAD,and Gini coefficients.The spatially constrained clustering and the risk relativity estimate help obtain a set of territory risk benchmarks used in rate filings to guide the rate regulation process.

Empirical Likelihood Based Goodness-of-fit Testing for Generalized Linear Mixed Models

In this paper, we propose a bias-corrected empirical likelihood （BCEL） ratio to construct a goodness- of-fit test for generalized linear mixed models. BCEL test maintains the advantage of empirical likelihood that is self scale invariant and then does not involve estimating limiting variance of the test statistic to avoid deteri- orating power of test. Furthermore, the bias correction makes the limit to be a process in which every variable is standard chi-squared. This simple structure of the process enables us to construct a Monte Carlo test proce- dure to approximate the null distribution. Thus, it overcomes a problem we encounter when classical empirical likelihood test is used, as it is asymptotically a functional of Gaussian process plus a normal shift function. The complicated covariance function makes it difficult to employ any approximation for the null distribution. The test is omnibus and power study shows that the test can detect local alternatives approaching the null at parametric rate. Simulations are carried out for illustration and for a comparison with existing method.

Investigating Trend in Cardiovascular Disease Mortality and Its Association with Obesity in the Gulf Cooperative Council (GCC) Countries from 1990 to 2019

Background: Cardiovascular diseases (CVDs) are the leading cause of death globally. An estimated 17.9 million people died from CVDs in 2019, representing 32% of all global deaths. Of these deaths, 85% were due to heart attack and stroke. Over three quarters of CVD deaths take place in low- and middle-income countries. We have studied the pattern of mortality due to cardiovascular in the six countries of the Arabian Gulf and its association with obesity over the 29 years 1990 to 2019. Methods: We used the linear mixed effect models to investigate the pattern of CVD mortality over the year 1990 to 2019, together with the pattern of change in one of the most important risk factors that is obesity, and its association with CVD mortality over the same period. Conclusions: Although there were fluctuations in the pattern of mortality and the prevalence of obesity over the specified period, there has been a steady decline in the per-100,000 number of deaths and the prevalence of obesity. However, there was a strong association between the two variables. From the fitted models we estimated that a one percent increase in obesity is associated with an average increase in cardiovascular deaths of 2.7 deaths per 100,000.

Impact of urbanization on morbidity of hepatitis A:a national panel study in China during 2005–2018

Background The effect of urbanization on the morbidity of hepatitis A remains unclear. We aimed to estimate the association between various urbanization-related indices and hepatitis A morbidity in China.Methods Data on the annual morbidity of hepatitis A, urbanization-related measures (i.e., gross domestic product per capita, the number of hospitalization beds per 1000 persons, illiteracy rate, tap water coverage, motor vehicles per 100 persons, population density, and the proportion of arable land), and meteorological factors in 31 provincial-level administrative divisions of Chinese mainland during 2005–2018 were collected from the National Population and Health Science Data Sharing Platform, China Statistical Yearbooks, and the China Meteorological Data Sharing Service System, respectively. Generalized linear mixed models were applied to quantify the impacts of different urbanization-related indices on the morbidity of hepatitis A in China after adjusting for covariates.Results A total of 537,466 hepatitis A cases were reported in China during 2005–2018. The annual morbidity had a decline of 79.4% from 5.64 cases to 1.16 cases per 100,000 people. There were obvious spatial variations with higher morbidity in western China. Nationally, gross domestic product per capita and the number of hospitalization beds per 1000 persons increased from 14,040 to 64,644 CNY and from 2.45 to 6.03 during 2005–2018, respectively. The illiteracy rate decreased from 11.0 to 4.9%. Gross domestic product per capita [relative risk (RR) = 0.96, 95% confidence interval (CI): 0.92–0.99], and the number of hospitalization beds per 1000 persons (RR = 0.79, 95%CI: 0.75–0.83) were associated with the declined morbidity of hepatitis A. By contrast, the increased morbidity of hepatitis A was linked to the illiteracy rate (RR = 1.04, 95%CI: 1.02–1.06). Similar influential factors were detected for children and adults, with greater effects witnessed for children.Conclusions People in the western region suffered the heaviest burden of hepatitis A in Chinese mainland. Nationally, there was a sharp decline in the morbidity of hepatitis A. The urbanization process was associated with the reduction of hepatitis A morbidity in China during 2005–2018.

Density dependence and habitat preference shape seedling survival in a subtropical forest in central China

Aims seedlings are vulnerable to many kinds of fatal abiotic and biotic agents,and examining the causes of seedling dynamics can help understand mechanisms of species coexistence.To disentangle the relative importance of neighborhood densities,habitat factors and phylogenetic relatedness on focal seedling survival,we monitored the survival of 5306 seedlings of 104 species>15 months.We address the following questions:(i)How do neighborhood densities,habitat variables and phylogenetic relatedness affect seedling survival?What is the relative importance of conspecific densities,habitat variables and phylogenetic relatedness to seedling survival?(ii)Does the importance of the neighborhood densities,habitat variables and phylogenetic relatedness vary among growth forms,leaf habits or dispersal modes?specially,does the conspecific negative density dependence inhibit tree and decidu-ous seedlings more compared with shrub and evergreen species?Does density dependence affect the wind and animal-dispersed species equally?Methods We established 135 census stations to monitor seedling dynamics in a 25-ha subtropical forest plot in central China.Conspecific and heterospecific seedling density in the 1-m2 seedling plot and adult basal area within a 20-m radius provided neighborhood density var-iables.mean elevation,convexity and aspect of every 5-×5-m grid with seedling plots were used to quantify habitat characteristics.We calculated the relative average phylodiversity between focal seed-ling and heterospecific neighbors to quantify the species related-ness in the neighborhood.Eight candidate generalized linear mixed models with binominal error distribution were used to compare the relative importance of these variables to seedling survival.akaike’s information criteria were used to identify the most parsimonious models.Important Findingsat the community level,both the neighborhood densities and phylogenetic relatedness were important to seedling survival.We found negative effects of increasing conspecific seedlings,which suggested the existence of species-specific density-dependent mortality.Phylodiversity of heterospecific neighbors was negatively related to survival of focal seedlings,indicating similar habitat preference shared among phylogenetically closely related species may drive seedling survival.The relative importance of neighborhood densities,habitat variables and phylogenetic relatedness varied among ecological guilds.Conspecific densities had significant negative effect for deciduous and wind-dispersed species,and marginally significant for tree seedlings>10 cm tall and animal-dispersed species.Habitat variables had limited effects on seedling survival,and only elevation was related to the sur-vival of evergreen species in the best-fit model.We conclude that both negative density-dependent mortality and habitat preference reflected by the phylogenetic relatedness shape the species coex-istence at seedling stage in this forest.

Landscape features and weather influence nest survival of a ground-nesting bird of conservation concern,the greater sage-grouse,in humanaltered environments

Introduction:Ground-nesting birds experience high levels of nest predation.However,birds can make selection decisions related to nest site location and characteristics that may result in physical,visual,and olfactory impediments to predators.Methods:We studied daily survival rate[DSR]of greater sage-grouse(Centrocercus urophasianus)from 2008 to 2010 in an area in Wyoming experiencing large-scale alterations to the landscape.We used generalized linear mixed models to model fixed and random effects,and a correlation within nesting attempts,individual birds,and years.Results:Predation of the nest was the most common source of nest failure(84.7%)followed by direct predation of the female(13.6%).Generally,landscape variables at the nest site(≤30 m)were more influential on DSR of nests than features at larger spatial scales.Percentage of shrub canopy cover at the nest site(15-m scale)and distances to natural gas wells and mesic areas had a positive relationship with DSR of nests,whereas distance to roads had a negative relationship with DSR of nests.When added to the vegetation model,maximum wind speed on the day of nest failure and a 1-day lag in precipitation(i.e.,precipitation the day before failure)improved model fit whereby both variables negatively influenced DSR of nests.Conclusions:Nest site characteristics that reduce visibility(i.e.,shrub canopy cover)have the potential to reduce depredation,whereas anthropogenic(i.e.,distance to wells)and mesic landscape features appear to facilitate depredation.Last,predators may be more efficient at locating nests under certain weather conditions(i.e.,high winds and moisture).