Deepwater Horizon oil spill exposure and child health: a longitudinal analysis

Population and Environment - The BP Deepwater Horizon oil spill (DHOS) created widespread concern about threats to health among residents of the Louisiana Gulf Coast. This study uses data from the...     

Dementia: challenges for social work education in Europe

ABSTRACT

Dementia has been identified as a global challenge across the spectrum of health and social care (World Health Organisation. (2012) Dementia: A public health priority. Geneva: WHO). This paper will explore the implications of this for social work education and the challenges it poses. There is a lack of this focus on social work with older people and people with dementia (pwd) in social work education. Based on calls for an infusion of content on ageing and dementia in social work curricula, paper proposes that we should adopt a person-centred philosophy alongside gerontological social work competencies to achieve this. The specific aim of this paper, therefore, is to explore how we can use these ideas as teaching tools to engage social work students in the discourse on dementia and to develop appropriate skills to work with pwd, their families and carers.     

Evaluating consumer satisfaction in residential continuing care settings

The outcome of the project reported on here is a client-centered consumer satisfaction questionnaire designed to evaluate new models of residential continuing care in Alberta, Canada. Satisfaction is defined as a multi-dimensional construct that is grounded in the consumer's experience. Consultation with the clients of the services during development of the instrument ensured that characteristics important to the clients were assessed. The result is an instrument with which to measure satisfaction that is fully client-centered and that, with appropriate modifications, can be used to monitor any client-centered program for cognitively-able continuing care clients.     

Deepwater Horizon Oil Spill Exposure,Industry Sector,and Child Health

Population Research and Policy Review - The historic 2010 BP Deepwater Horizon Oil Spill (DHOS) led to public distress regarding potential impacts on children in nearby Gulf Coast communities....     

Estimators of percentiles based on absolute loss

Estimators of percentiles of location and scale parameter distributions are optimized based on Pitman closeness and absolute risk. A median unbiased (MU) estimator and a minimum risk (MR) estimator are shown to exist within a class of estimators, and to depend upon the medians of two completely specified distributions.     

Correlation-Type Goodness of Fit Test for Extreme Value Distribution Based on Simultaneous Closeness

In reliability studies, one typically would assume a lifetime distribution for the units under study and then carry out the required analysis. One popular choice for the lifetime distribution is the family of two-parameter Weibull distributions (with scale and shape parameters) which, through a logarithmic transformation, can be transformed to the family of two-parameter extreme value distributions (with location and scale parameters). In carrying out a parametric analysis of this type, it is highly desirable to be able to test the validity of such a model assumption. A basic tool that is useful for this purpose is a quantile–quantile (QQ) plot, but in its use, the issue of the choice of plotting position arises. Here, by adopting the optimal plotting points based on Pitman closeness criterion proposed recently by Balakrishnan et al. (2010b Balakrishnan , N. , Davies , K. F. , Keating , J. P. , Mason , R. L. ( 2010b ). Computation of optimal plotting points based on Pitman Closeness with an application to goodness of fit for location-scale families. Submitted to Computational Statistics & Data Analysis.  [Google Scholar]), and referred to as simultaneous closeness probability (SCP) plotting points, we propose a correlation-type goodness of fit test for the extreme value distribution. We compute the SCP plotting points for various sample sizes and use them to determine the mean, standard deviation and critical values for the proposed correlation-type test statistic. Using these critical values, we carry out a power study, similar to the one carried out by Kinnison (1989 Kinnison , R. ( 1989 ). Correlation coefficient goodness of fit test for extreme value distribution . The American Statistician 43 : 98 – 100 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]), through which we demonstrate that the use of SCP plotting points results in better power than with the use of mean ranks as plotting points and nearly the same power as with the use of median ranks. We then demonstrate the use of the SCP plotting points and the associated correlation-type test for Weibull analysis with an illustrative example. Finally, for the sake of comparison, we also adapt two statistics proposed by Gan and Koehler (1990 Gan , F. F. , Koehler , K. J. ( 1990 ). Goodness of fit based on P-P probability plots . Technometrics 32 : 289 – 303 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]), in the context of probability–probability (PP) plots, based on SCP plotting points and compare their performance to those based on mean ranks. The empirical study also reveals that the tests from the QQ plot have better power than those from the PP plot.     

On simultaneous closeness probabilities of order statistics from odd sample sizes to the population median

In this note, we present alternative derivations for the probability that an individual order statistic is closest to the target parameter among all order statistics from a complete random sample. This approach is simpler than the geometric arguments used earlier. We also provide a simple direct proof for the symmetry property of the simultaneous closeness probabilities among order statistics for the estimation of percentiles from a symmetric family. Finally, we offer an alternative simpler proof for the result that sample medians from larger odd sample sizes are Pitman closer to the population median than sample medians from smaller odd sample sizes.     

An adaptive estimatcr frequently used in material fatigue testing

Small sample sizes in material fatigue tests give rise to an adaptive estimator of the 100(1-P)% normal percentile, which is the 100P% survival load. The mean squared relative efficiency of the best invariant estimator of normal percentiles to the adaptive estimator is dependent upon the unknown parameters only through the coefficient of variation. The adaptive estimator is shown to be more locally efficient than tl-:ebest invariant estimator over a subset of the parameter space. However, in the extreme values of P the coverage probabilities of the adaptive estimator provide little more protection than a traditional point estimator over the range of preference based on mean squared relative efficiency.     

Misattributions to crowding: Blaming crowding for nondensity-caused events

Three field studies and a laboratory experiment investigated the effects of disconfirmed expectations and unattained goals, varying independently of density, on attributions to crowding. Studies 1 and 2 found that positively and negatively disconfirmed time expectations elicited greater attributions to crowding than confirmed time expectations. The second field study also showed that students not attaining their course registration goals made stronger crowding attributions than students who obtained their desired courses. The expectancy disconfirmation results were replicated in a laboratory experiment. Disconfirmed performance expectations, whether positive or negative, produced stronger attributions to crowding than confirmed expectations. The final study in this series demonstrated that crowding attributions can occur despite the presence of other plausible environmental and nonenvironmental causal factors. Taken together, these results show that factors operating independently of density can influence crowding attributions in high-density environments.