Improved Transferability of Data‐Driven Damage Models Through Sample Selection Bias Correction

Damage models for natural hazards are used for decision making on reducing and transferring risk. The damage estimates from these models depend on many variables and their complex sometimes nonlinear relationships with the damage. In recent years, data‐driven modeling techniques have been used to capture those relationships. The available data to build such models are often limited. Therefore, in practice it is usually necessary to transfer models to a different context. In this article, we show that this implies the samples used to build the model are often not fully representative for the situation where they need to be applied on, which leads to a “sample selection bias.” In this article, we enhance data‐driven damage models by applying methods, not previously applied to damage modeling, to correct for this bias before the machine learning (ML) models are trained. We demonstrate this with case studies on flooding in Europe, and typhoon wind damage in the Philippines. Two sample selection bias correction methods from the ML literature are applied and one of these methods is also adjusted to our problem. These three methods are combined with stochastic generation of synthetic damage data. We demonstrate that for both case studies, the sample selection bias correction techniques reduce model errors, especially for the mean bias error this reduction can be larger than 30%. The novel combination with stochastic data generation seems to enhance these techniques. This shows that sample selection bias correction methods are beneficial for damage model transfer.     

Low dose risk estimation via simultaneous statistical inferences

Summary.  The paper develops and studies simultaneous confidence bounds that are useful for making low dose inferences in quantitative risk analysis. Application is intended for risk assessment studies where human, animal or ecological data are used to set safe low dose levels of a toxic agent, but where study information is limited to high dose levels of the agent. Methods are derived for estimating simultaneous, one-sided, upper confidence limits on risk for end points measured on a continuous scale. From the simultaneous confidence bounds, lower confidence limits on the dose that is associated with a particular risk (often referred to as a bench-mark dose ) are calculated. An important feature of the simultaneous construction is that any inferences that are based on inverting the simultaneous confidence bounds apply automatically to inverse bounds on the bench-mark dose.     

Benchmark Analysis: Shopping with Proper Confidence

We discuss the issue of using benchmark doses for quantifying (excess) risk associated with exposure to environmental hazards. The paradigm of low-dose risk estimation in dose-response modeling is used as the primary application scenario. Emphasis is placed on making simultaneous inferences on benchmark doses when data are in the form of proportions, although the concepts translate easily to other forms of outcome data.     

Human Salmonellosis: Estimation of Dose-Illness from Outbreak Data

The quantification of the relationship between the amount of microbial organisms ingested and a specific outcome such as infection, illness, or mortality is a key aspect of quantitative risk assessment. A main problem in determining such dose-response models is the availability of appropriate data. Human feeding trials have been criticized because only young healthy volunteers are selected to participate and low doses, as often occurring in real life, are typically not considered. Epidemiological outbreak data are considered to be more valuable, but are more subject to data uncertainty. In this article, we model the dose-illness relationship based on data of 20 Salmonella outbreaks, as discussed by the World Health Organization. In particular, we model the dose-illness relationship using generalized linear mixed models and fractional polynomials of dose. The fractional polynomial models are modified to satisfy the properties of different types of dose-illness models as proposed by Teunis et al . Within these models, differences in host susceptibility (susceptible versus normal population) are modeled as fixed effects whereas differences in serovar type and food matrix are modeled as random effects. In addition, two bootstrap procedures are presented. A first procedure accounts for stochastic variability whereas a second procedure accounts for both stochastic variability and data uncertainty. The analyses indicate that the susceptible population has a higher probability of illness at low dose levels when the combination pathogen-food matrix is extremely virulent and at high dose levels when the combination is less virulent. Furthermore, the analyses suggest that immunity exists in the normal population but not in the susceptible population.     

African American family life in societal context: Crisis and hope

Since 1965 hundreds of articles and books have been published about African American families. Nevertheless, our understanding of these families continues to be limited. There is a tendency to gloss over important within-group differences; thus, monolithic, stereotypic and inaccurance portrayals of Black family life are common. This paper sets aside debates of Black family pathology or viability, focusing instead on these families' essential character. The paper seeks to understand Black families on their own terms, locating them in relevant social, historical, political and cultural contexts. Key empirical patterns and trends reveal dramatic changes in Black family geographic location, headship, quality of life and socioeconomic status since 1950.A complex picture is revealed. There has been gradual but steady overall improvement alongside persistent, extreme racial disparties and pronounced class disparities among Black families. The proposed Black Family Socio-Ecological Context model specifies and connects institutional, interpersonal, environmental, temporal and cultural facts that shape the essential character of Black family life in such a way as to produce characteristics simultaneously shared and idiosyncratic. The model also provides an organized, systematic accounting of research and public policy issues relevant to the study of African American families.An early version co-authored with Richard A. English was presented during the National Council on Family Relations Meetings in Portland, Oregon, October 1980.     

Exploration to Foster Career Development

Responses to the Adult Career Concerns Inventory (ACCI: Super, Thompson, Lindeman, Myers, & Jordaan, 1988) were organized through cluster analysis to identify different ways in which adults use exploratory behavior to cope with career development tasks. Significant differences in life-role salience among the types of adult career explorers identified were also investigated. Findings indicated a variety of ways in which adults use exploratory behavior. However, no significant differences were found in life-role salience among the types of career explorers. The discussion explains how career counselors can interpret their clients' ACCI profiles to select appropriate career interventions.     

Met needs and unmet needs, and satisfaction among Social HMO members

This article reports on a survey of 800 members of four Social HMO demonstration sites, who were receiving home-based, community-based, and short-term institutional services under the demonstration's expanded community care benefits. The survey asked whether members needed help in 11 areas, whether they received help in each area from an informal caregiver, whether they wanted more help from the Social HMO, and whether help provided by both was adequate. Satisfaction with the program and with service coordination was also assessed. The adequacy of informal care differed by problem area, as did the help desired from the Social HMO and its responsiveness. Members were less satisfied when they had weaker informal care, were African American, and when they received inadequate help from the plan with ADLs, transportation, medical access, and managing money. Members were more satisfied when they were professionals, home owners, knew their service coordinator's name (or how to contact her), and received help with their problems. The findings point to the importance of clarifying divisions of labor with informal caregivers, as well as possible expansions in responsibilities for service coordinators and benefits beyond traditional boundaries.