Working Together Apart

In this paper we report upon the development and operation of a “street-level” response to the problems of interprofessional joint working in providing appropriate care for elderly people living in one Scottish city. The “exchange system”, as it was known in the locale, was a mechanism for co-ordinating the movement of elderly people between the geriatric, psychiatric, and residential services within the city in response to changes in the needs of the individual elderly person, and the needs of service providers. The importance of the scheme stemmed from the fact that it was not imposed on professionals' work, but rather that it developed out of that work. By focusing on the operation of interprofessional joint working at the street level we draw attention to those complexities involved in such work which are often overlooked in the broad policy statements on joint working which have emerged from government departments, and health and social services agencies. Policy makers and analysts alike have largely ignored the meaning and consequences of joint working at the level of professionals' actual work, and it is this lacuna in the literature that the paper seeks to address. The paper concludes with an appeal to researchers and practitioners to describe any such schemes of whatever nature operating in their own locales. In so doing a corpus of knowledge looking critically at the experience of interservice and interprofessional collaboration at the street level may emerge which would inform broad policy statements.     

Talking about Beauty: A Study of Everyday Aesthetics among Low‐Income Citizens of Milan

This paper reports on research undertaken into the aesthetics of the everyday. As well as the subject matter of aesthetic philosophy, art criticism and of the sociology of art, beauty, and beautiful are of course very ordinary matters too. To shed light on the meanings of beauty as used in everyday settings and in natural language, we use the data collected in a study conducted with a group of low‐income residents of the city of Milan. In this study we were interested in analyzing their lifestyle in terms of their relationship with aesthetics, i.e., with “beautiful” objects and/or experiences. Participants' self‐reported aesthetic appreciations suggest that conceptions of “beauty” are used as devices to narrate pieces of identity, memories, experiences, etc. Their aesthetic judgements take on an anthropological function, creating a framework of meanings that help the participants make sense of the world of objects and of their own lives with/through them.     

Migration is the Driving Force of Rapid Aging in Puerto Rico: A Research Brief

Population Research and Policy Review - The combined effects of declining fertility and increased longevity have accelerated population aging in different parts of the world. Unlike other...     

Modification of the kolmogorov-smirnov test for the erlang-2 distribution

An adjusted Kolmogorov-Smirnov statistic and critical values are developed for the Erlang-2 probability distribution using data from Monte Carlo simulations. The process used is similar to that of Stephens in the 1970s. The test statistic produced features of compactness and ease of implementation. It is quite accurate for sample sizes as low as ten.     

Accurate and efficient numerical calculation of stable densities via optimized quadrature and asymptotics

Stable distributions are an important class of infinitely divisible probability distributions, of which two special cases are the Cauchy distribution and the normal distribution. Aside from a few special cases, the density function for stable distributions has no known analytic form and is expressible only through the variate’s characteristic function or other integral forms. In this paper, we present numerical schemes for evaluating the density function for stable distributions, its gradient, and distribution function in various parameter regimes of interest, some of which had no preexisting efficient method for their computation. The novel evaluation schemes consist of optimized generalized Gaussian quadrature rules for integral representations of the density function, complemented by asymptotic expansions near various values of the shape and argument parameters. We report several numerical examples illustrating the efficiency of our methods. The resulting code has been made available online.     

Data‐driven treatment selection for seamless phase II/III trials incorporating early‐outcome data

Seamless phase II/III clinical trials are conducted in two stages with treatment selection at the first stage. In the first stage, patients are randomized to a control or one of k > 1 experimental treatments. At the end of this stage, interim data are analysed, and a decision is made concerning which experimental treatment should continue to the second stage. If the primary endpoint is observable only after some period of follow‐up, at the interim analysis data may be available on some early outcome on a larger number of patients than those for whom the primary endpoint is available. These early endpoint data can thus be used for treatment selection. For two previously proposed approaches, the power has been shown to be greater for one or other method depending on the true treatment effects and correlations. We propose a new approach that builds on the previously proposed approaches and uses data available at the interim analysis to estimate these parameters and then, on the basis of these estimates, chooses the treatment selection method with the highest probability of correctly selecting the most effective treatment. This method is shown to perform well compared with the two previously described methods for a wide range of true parameter values. In most cases, the performance of the new method is either similar to or, in some cases, better than either of the two previously proposed methods. © 2014 The Authors. Pharmaceutical Statistics published by John Wiley & Sons Ltd.     

Likelihood Inference for Discretely Observed Nonlinear Diffusions

This paper is concerned with the Bayesian estimation of nonlinear stochastic differential equations when observations are discretely sampled. The estimation framework relies on the introduction of latent auxiliary data to complete the missing diffusion between each pair of measurements. Tuned Markov chain Monte Carlo (MCMC) methods based on the Metropolis‐Hastings algorithm, in conjunction with the Euler‐Maruyama discretization scheme, are used to sample the posterior distribution of the latent data and the model parameters. Techniques for computing the likelihood function, the marginal likelihood, and diagnostic measures (all based on the MCMC output) are developed. Examples using simulated and real data are presented and discussed in detail.