Receipt of Formal and Informal Help with Specific Care Tasks among Older People Living in their Own Home. National Trends over Two Decades

Sweden is seen as a typical example of a social democratic welfare regime, with universal and generous welfare policies. However, in the last decades, there have been substantial reductions in the Swedish provision of care for older people. This study aimed to examine trends in sources of care‐receipt in older people (77+) living in their own home and with a perceived need for help with two specific tasks: house cleaning and/or food shopping. Trends in care‐receipt were examined in relation to gender, living alone, having children and socio‐economic position. Data from the 1992, 2002 and 2011 data collection waves of the national study, Swedish Panel Study of Living Conditions of the Oldest Old (SWEOLD), were used. Response rates varied between 86 and 95 per cent, and the sample represents the population well. Trends and differences between groups were explored in bivariate and logistic regression analyses. There was a reduction in formal care‐receipt regarding house cleaning and food shopping over the study period. It was more common for women than men to receive formal care, and more common for men than women to receive informal care. Reductions in formal care have affected older women more than older men. Still, living alone was the most influential factor in care‐receipt, associated with a greater likelihood of formal care‐receipt and a lower likelihood of informal care‐receipt. It can be concluded that public responsibility for care is becoming more narrowly defined in Sweden, and that more responsibility for care is placed on persons in need of care and their families.     

Empirical Likelihood Inference for the Rao‐Hartley‐Cochran Sampling Design

The Hartley‐Rao‐Cochran sampling design is an unequal probability sampling design which can be used to select samples from finite populations. We propose to adjust the empirical likelihood approach for the Hartley‐Rao‐Cochran sampling design. The approach proposed intrinsically incorporates sampling weights, auxiliary information and allows for large sampling fractions. It can be used to construct confidence intervals. In a simulation study, we show that the coverage may be better for the empirical likelihood confidence interval than for standard confidence intervals based on variance estimates. The approach proposed is simple to implement and less computer intensive than bootstrap. The confidence interval proposed does not rely on re‐sampling, linearization, variance estimation, design‐effects or joint inclusion probabilities.     

Trying to stay ahead of the curve in Chile's economic development: exploring a way out of the middle‐income trap through pragmatic export development

Underneath impressive growth levels, the Chilean economy displays signs of being caught in a middle‐income trap. It has been unable to improve its productivity, increase the added value of its exports or upgrade its value chain. Its economy cannot compete either with low‐wage countries or highly productive, innovative countries. Its export strategy based on export promotion seems to have outlived its usefulness. It achieved remarkable quantitative success, but must now attend qualitative attributes. Instead of regarding market‐driven export promotion and state‐led export development as substitutes, this article proposes to view them as alternatives in different stages of development. To choose the appropriate time, more attention should be given to non‐traditional, structural indicators, like export sophistication and political‐institutional capabilities.     

Bayesian bridge-randomized penalized quantile regression estimation for linear regression model with AP(q) perturbation

Bridge penalized regression has many desirable statistical properties such as unbiasedness, sparseness as well as ‘oracle’. In Bayesian framework, bridge regularized penalty can be implemented based on generalized Gaussian distribution (GGD) prior. In this paper, we incorporate Bayesian bridge-randomized penalty and its adaptive version into the quantile regression (QR) models with autoregressive perturbations to conduct Bayesian penalization estimation. Employing the working likelihood of the asymmetric Laplace distribution (ALD) perturbations, the Bayesian joint hierarchical models are established. Based on the mixture representations of the ALD and generalized Gaussian distribution (GGD) priors of coefficients, the hybrid algorithms based on Gibbs sampler and Metropolis-Hasting sampler are provided to conduct fully Bayesian posterior estimation. Finally, the proposed Bayesian procedures are illustrated by some simulation examples and applied to a real data application of the electricity consumption.     

Myths and realities about input subsidies in sub‐Saharan Africa

Using a recent public expenditure dataset, this article proposes a ‘reality check’ of the level and composition of input subsidies in nine African countries between 2006 and 2013. Results show that input subsidies (1) received close to 35% of agricultural‐specific expenditure on average and (2) cover a variety of interventions, including investments in capital, such as on‐farm irrigation, and in on‐farm services, such as inspection or training. Further, the figures show that input subsidies tended to become entrenched in agricultural budgets over time, leading to sub‐optimal execution rates, and were primarily funded by the national taxpayer, while donors invested more in public goods. Findings confirm that input subsidies crowded out other spending categories likely to be more supportive of long‐term agricultural development objectives. The article concludes that the political economy of input subsidies should be directed to making more concrete efforts to attain a better balance of public expenditure on agriculture. Furthermore, policy‐makers should aim to increase the efficiency and policy coherence of input subsidies, since merely abolishing them is likely to be unfeasible in the short term.     

基于支持向量机的管理信息系统故障识别模型研究

管理信息系统故障影响着企业信息工程的开展。及时识别故障,能够为企业争取更多时间处理故障。因此,管理信息系统故障识别有着重要的研究意义和实践意义。基于支持向量机,构建管理信息系统故障识别模型,通过把样本应用于该模型,结果表明该模型具有较好的准确性,能有效识别管理信息系统故障。     

A Tiered Framework for Risk‐Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children's Study (NCS)

A challenge for large‐scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co‐occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure‐relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new “Tiered Exposure Ranking” (TiER) framework, developed to support various aspects of risk‐relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both “discovery‐driven” and “hypothesis‐driven” analyses. “Tier 1” applications focus on “exposomic” pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk‐relevant exposure metrics for populations and individuals. In this article, “tier 1” applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A “tier 2” application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk‐relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.     

Optimal design of repetitive group sampling plans for Weibull and gamma distributions with applications and comparison to the Birnbaum–Saunders distribution

In this paper, we propose a multiple deferred state repetitive group sampling plan which is a new sampling plan developed by incorporating the features of both multiple deferred state sampling plan and repetitive group sampling plan, for assuring Weibull or gamma distributed mean life of the products. The quality of the product is represented by the ratio of true mean life and specified mean life of the products. Two points on the operating characteristic curve approach is used to determine the optimal parameters of the proposed plan. The plan parameters are determined by formulating an optimization problem for various combinations of producer's risk and consumer's risk for both distributions. The sensitivity analysis of the proposed plan is discussed. The implementation of the proposed plan is explained using real-life data and simulated data. The proposed plan under Weibull distribution is compared with the existing sampling plans. The average sample number (ASN) of the proposed plan and failure probability of the product are obtained under Weibull, gamma and Birnbaum–Saunders distributions for a specified value of shape parameter and compared with each other. In addition, a comparative study is made between the ASN of the proposed plan under Weibull and gamma distributions.     

Response‐adaptive designs for binary responses: How to offer patient benefit while being robust to time trends?

Response‐adaptive randomisation (RAR) can considerably improve the chances of a successful treatment outcome for patients in a clinical trial by skewing the allocation probability towards better performing treatments as data accumulates. There is considerable interest in using RAR designs in drug development for rare diseases, where traditional designs are not either feasible or ethically questionable. In this paper, we discuss and address a major criticism levelled at RAR: namely, type I error inflation due to an unknown time trend over the course of the trial. The most common cause of this phenomenon is changes in the characteristics of recruited patients—referred to as patient drift. This is a realistic concern for clinical trials in rare diseases due to their lengthly accrual rate. We compute the type I error inflation as a function of the time trend magnitude to determine in which contexts the problem is most exacerbated. We then assess the ability of different correction methods to preserve type I error in these contexts and their performance in terms of other operating characteristics, including patient benefit and power. We make recommendations as to which correction methods are most suitable in the rare disease context for several RAR rules, differentiating between the 2‐armed and the multi‐armed case. We further propose a RAR design for multi‐armed clinical trials, which is computationally efficient and robust to several time trends considered.     

The struggle for Via Bologna street market: crisis,racial denial and speaking back to power in Naples Italy

This paper is based on ethnographic research conducted with migrant and Italian street vendors in Naples, southern Italy, in 2012. It tells the story of Via Bologna market which was nearly closed down by the City Hall at the time. Naples is a city where issues of poverty and unemployment pre‐date and have been exacerbated by manifold narratives of crisis now unfolding across Europe regarding the economy, political legitimacy, security and migration. Street markets have always been an important and visible economic survival strategy for both Neapolitans and migrants there. This article shows how the Via Bologna street vendors appropriated and adapted discourses about crisis to form their own cosmopolitan social movement that halted the closure of the market. It argues that, in the age of globalized migration, the multilingual nature of such collective action is central to understanding social struggles that must be organized between marginalized groups of people divided by race, religion, politics and legal status. This, frequently ambiguous, transcultural solidarity speaks back against a mainstream post‐racial discourse – often articulated by the Neapolitan street vendors at the market – that would reduce the complexity of such collective action to questions of poverty and class struggle.