Mastery,Homeownership, and Adult Roles During the Transition to Adulthood

We investigate the relationship between homeownership and personal sense of mastery in the transition to adulthood and examine whether three important adult transitions (employment, marriage/cohabitation, and parenthood) moderate the impact of homeownership on mastery. Utilizing the National Longitudinal Survey of Youth—Young Adult Sample (N = 1,609), we estimate change models to assess the direct effects of homeownership on mastery as well as whether this impact is modified by the transition to adult roles. Homeownership increases the sense of mastery among young adults. Homeowners who are unemployed paradoxically receive a boost to mastery not experienced by those who are employed, and homeowners who are parents experience increased mastery, compared to those who do not have children. Owning a home has a positive influence on young adults' sense of mastery during a period when their mastery is in flux and they are accumulating new roles.     

On An Intriguing Distributional Identity

For a continuous random variable X with support equal to (a, b), with c.d.f. F, and g: Ω₁ → Ω₂ a continuous, strictly increasing function, such that Ω₁∩Ω₂?(a, b), but otherwise arbitrary, we establish that the random variables F(X) ? F(g(X)) and F(g^{? 1}(X)) ? F(X) have the same distribution. Further developments, accompanied by illustrations and observations, address as well the equidistribution identity U ? ψ(U) = ^dψ^{? 1}(U) ? U for U ～ U(0, 1), where ψ is a continuous, strictly increasing and onto function, but otherwise arbitrary. Finally, we expand on applications with connections to variance reduction techniques, the discrepancy between distributions, and a risk identity in predictive density estimation.     

Bayesian estimation of reliability using time-to-failure distribution of parametric degradation models

This paper focusses on computing the Bayesian reliability of components whose performance characteristics (degradation – fatigue and cracks) are observed during a specified period of time. Depending upon the nature of degradation data collected, we fit a monotone increasing or decreasing function for the data. Since the components are supposed to have different lifetimes, the rate of degradation is assumed to be a random variable. At a critical level of degradation, the time to failure distribution is obtained. The exponential and power degradation models are studied and exponential density function is assumed for the random variable representing the rate of degradation. The maximum likelihood estimator and Bayesian estimator of the parameter of exponential density function, predictive distribution, hierarchical Bayes approach and robustness of the posterior mean are presented. The Gibbs sampling algorithm is used to obtain the Bayesian estimates of the parameter. Illustrations are provided for the train wheel degradation data.     

Hypothesis Tests for Neyman's Bias in Case–Control Studies

Survival bias is a long recognized problem in case–control studies, and many varieties of bias can come under this umbrella term. We focus on one of them, termed Neyman's bias or ‘prevalence–incidence bias’. It occurs in case–control studies when exposure affects both disease and disease-induced mortality, and we give a formula for the observed, biased odds ratio under such conditions. We compare our result with previous investigations into this phenomenon and consider models under which this bias may or may not be important. Finally, we propose three hypothesis tests to identify when Neyman's bias may be present in case–control studies. We apply these tests to three data sets, one of stroke mortality, another of brain tumors, and the last of atrial fibrillation, and find some evidence of Neyman's bias in the former two cases, but not the last case.     

Aerodynamic roughness variation with vegetation: analysis in a suburban neighbourhood and a city park

Urban Ecosystems - Local aerodynamic roughness parameters (zero-plane displacement, z d , and aerodynamic roughness length, z 0 ) are determined for an urban park and a suburban neighbourhood with...     

Deep Uncertainties in Sea-Level Rise and Storm Surge Projections: Implications for Coastal Flood Risk Management

Sea levels are rising in many areas around the world, posing risks to coastal communities and infrastructures. Strategies for managing these flood risks present decision challenges that require a combination of geophysical, economic, and infrastructure models. Previous studies have broken important new ground on the considerable tensions between the costs of upgrading infrastructure and the damages that could result from extreme flood events. However, many risk-based adaptation strategies remain silent on certain potentially important uncertainties, as well as the tradeoffs between competing objectives. Here, we implement and improve on a classic decision-analytical model (Van Dantzig 1956) to: (i) capture tradeoffs across conflicting stakeholder objectives, (ii) demonstrate the consequences of structural uncertainties in the sea-level rise and storm surge models, and (iii) identify the parametric uncertainties that most strongly influence each objective using global sensitivity analysis. We find that the flood adaptation model produces potentially myopic solutions when formulated using traditional mean-centric decision theory. Moving from a single-objective problem formulation to one with multiobjective tradeoffs dramatically expands the decision space, and highlights the need for compromise solutions to address stakeholder preferences. We find deep structural uncertainties that have large effects on the model outcome, with the storm surge parameters accounting for the greatest impacts. Global sensitivity analysis effectively identifies important parameter interactions that local methods overlook, and that could have critical implications for flood adaptation strategies.     

The Interview for Decisional Abilities (IDA): a tool to assess the decisional capacity of abused and neglected older adults

We present the Interview for Decisional Abilities (IDA), a semi-structured tool for use by adult protective services (APS) workers as part of their comprehensive assessments of clients. The IDA was created in response to a Federal mandate to standardize the procedures and competencies of APS agencies with a view to improving client assessments and facilitating cross-jurisdictional research on adult mistreatment. The proximal aim of the IDA is to guide workers in gathering information on the ability of suspected victims of adult mistreatment to make decisions about the risks they face.