Bayesian analysis of discrete time warranty data

Summary.  The analysis of warranty claim data, and their use for prediction, has been a topic of active research in recent years. Field data comprising numbers of units returned under guarantee are examined, covering both situations in which the ages of the failed units are known and in which they are not. The latter case poses particular computational problems for likelihood-based methods because of the large number of feasible failure patterns that must be included as contributions to the likelihood function. For prediction of future warranty exposure, which is of central concern to the manufacturer, the Bayesian approach is adopted. For this, Markov chain Monte Carlo methodology is developed.     

A Multivariate Model for Repeated Failure Time Measurements

A parametric multivariate failure time distribution is derived from a frailty-type model with a particular frailty distribution. It covers as special cases certain distributions which have been used for multivariate survival data in recent years. Some properties of the distribution are derived: its marginal and conditional distributions lie within the parametric family, and association between the component variates can be positive or, to a limited extent, negative. The simple closed form of the survivor function is useful for right-censored data, as occur commonly in survival analysis, and for calculating uniform residuals. Also featured is the distribution of ratios of paired failure times. The model is applied to data from the literature     

Reasoning Together Through Telling Stories: How People Talk about Social Controversies

Qualitative Sociology - We use focus groups of ordinary citizens talking about social controversies to analyze the role of storytelling in collective reasoning. Prior research has emphasized...     

Patterns of pollinator turnover and increasing diversity associated with urban habitats

The role of urban expansion on bee diversity is poorly understood, but it may play an important role in restructuring pollinator diversity observed in rural regions at the urban perimeter. We studied bee communities in two habitats essential for pollinators (residential gardens and semi-natural areas) at 42 sites situated at the edge of greater Montreal, Canada. Bee species richness, abundance and functional diversity all increased with urbanization in both habitat types, but gardens and semi-natural areas supported distinct bee communities with unique responses to urbanization in terms of species turnover. Compared to semi-natural sites, residential gardens supported bees that foraged from a greater number but a lower proportion of available plant species. Bees did not discriminate between exotic and indigenous plant species in either gardens or semi-natural sites and were attracted to flowers in either habitat irrespective of their origins. Protecting semi-natural ruderal areas and providing residential garden habitats for pollinators are both effective means of promoting regional bee diversity in urbanizing regions.     

Influence of Proximity to Kin on Residential Mobility and Destination Choice: Examining Local Movers in Metropolitan Areas

A growing body of research has examined how family dynamics shape residential mobility, highlighting the social—as opposed to economic—drivers of mobility. However, few studies have examined kin ties as both push and pull factors in mobility processes or revealed how the influence of kin ties on mobility varies across sociodemographic groups. Using data on local residential moves from the Panel Study of Income Dynamics (PSID) from 1980 to 2013, we find that location of noncoresident kin influences the likelihood of moving out of the current neighborhood and the selection of a new destination neighborhood. Analyses of out-mobility reveal that parents and young adult children living near each other as well as low-income adult children living near parents are especially deterred from moving. Discrete-choice models of neighborhood selection indicate that movers are particularly drawn to neighborhoods close to aging parents, white and higher-income households tend to move close to parents and children, and lower-income households tend to move close to extended family. Our results highlight the social and economic trade-offs that households face when making residential mobility decisions, which have important implications for broader patterns of inequality in residential attainment.     

Metropolitan Heterogeneity and Minority Neighborhood Attainment: Spatial Assimilation or Place Stratification?

Using geo-referenced data from the Panel Study of Income Dynamics, in conjunction with decennial census data, this research examines metropolitan-area variation in the ability of residentially mobile blacks, Hispanics, and whites to convert their income into two types of neighborhood outcomes-neighborhood racial composition and neighborhood socioeconomic status. For destination tract racial composition, we find strong and near-universal support for the "weak version" of place stratification theory; relative to whites, the effect of individual income on the percent of the destination tract population that is non-Hispanic white is stronger for blacks and Hispanics, but even the highest earning minority group members move to tracts that are "less white" than the tracts that the highest-earning whites move to. In contrast, for moves into neighborhoods characterized by higher levels of average family income, we find substantial heterogeneity across metropolitan areas in minorities' capacity to convert income into neighborhood quality. A slight majority of metropolitan areas evince support for the "strong version" of place stratification theory, in which blacks and Hispanics are less able than whites to convert income into neighborhood socioeconomic status. However, a nontrivial number of metropolitan areas also evince support for spatial assimilation theory, where the highest-earning minorities achieve neighborhood parity with the highest-earning whites. Several metropolitan-area characteristics, including residential segregation, racial and ethnic composition, immigrant population size, poverty rates, and municipal fragmentation, emerge as significant predictors of minority-white differences in neighborhood attainment.     

Temporal variation in the relationship between environmental demands and well-being: a panel analysis of developed and less-developed countries

This study assesses the degree to which the relationship between the environmental demands of countries (measured as ecological footprint per capita) and well-being (measured as life expectancy) has changed over the last several decades (1961–2007) and whether the nature and extent of these changes differ between developed and less-developed countries. Pooled ordinary least squares regression results indicate that decoupling has occurred among developed countries, where the relationship between ecological footprint and life expectancy weakened substantially over time, becoming negative in later years. In less-developed countries, the relationship has intensified substantially, with the effect of ecological footprint on life expectancy becoming stronger over time. Fixed-effects regression results provide similar results for developed countries but indicate slight decoupling between increases in ecological footprint and life expectancy among less-developed countries. The implications of these results are discussed in the context of contraction and convergence approaches to sustainability.     

Using In Vitro High‐Throughput Screening Data for Predicting Benzo[k]Fluoranthene Human Health Hazards

Today there are more than 80,000 chemicals in commerce and the environment. The potential human health risks are unknown for the vast majority of these chemicals as they lack human health risk assessments, toxicity reference values, and risk screening values. We aim to use computational toxicology and quantitative high‐throughput screening (qHTS) technologies to fill these data gaps, and begin to prioritize these chemicals for additional assessment. In this pilot, we demonstrate how we were able to identify that benzo[k]fluoranthene may induce DNA damage and steatosis using qHTS data and two separate adverse outcome pathways (AOPs). We also demonstrate how bootstrap natural spline‐based meta‐regression can be used to integrate data across multiple assay replicates to generate a concentration–response curve. We used this analysis to calculate an in vitro point of departure of 0.751 μM and risk‐specific in vitro concentrations of 0.29 μM and 0.28 μM for 1:1,000 and 1:10,000 risk, respectively, for DNA damage. Based on the available evidence, and considering that only a single HSD17B4 assay is available, we have low overall confidence in the steatosis hazard identification. This case study suggests that coupling qHTS assays with AOPs and ontologies will facilitate hazard identification. Combining this with quantitative evidence integration methods, such as bootstrap meta‐regression, may allow risk assessors to identify points of departure and risk‐specific internal/in vitro concentrations. These results are sufficient to prioritize the chemicals; however, in the longer term we will need to estimate external doses for risk screening purposes, such as through margin of exposure methods.     

Missing millions: undercounting urbanization in India

Population and Environment - The measurement and characterization of urbanization crucially depends upon defining what counts as urban. The government of India estimates that only 31% of the...