Consumption and poverty in the homes of the English poor,c. 1670–1834

The consumer behaviour of the poor in the long eighteenth century has attracted more historical attention in recent years. Yet, we have little understanding of whether regional factors affected consumption or how the poor’s ownership of household goods was influenced by level of poverty and the life-cycle. By focusing on Kent and drawing comparisons to other counties, this article argues that the material lives of the poor were improving by the late eighteenth century, but finds that there were distinct regional differences as the poor acquired more and better goods in London and the Home Counties than in relatively remote areas. Moreover, by using pauper inventories and labourers’ probate inventories, the research finds that the poor were not a homogeneous group with similar levels of material wealth, but should be considered in terms of different subgroups which often led very different material lives to one another due to life-cycle-related problems including sickness and old age. Labourers’ probate inventories are found to represent a minority of the poor who were materially richer than most, whilst pauper inventories appear to represent a more typical subgroup of the poor that struggled to make do and owned most types of goods in smaller numbers.     

《麦克白》咒语现象解析

咒语现象是《麦克白》整出戏剧极富魅力的表现元素。它既为剧本奠定了一种神秘而阴森的基调,同时确定全局总纲,为剧情发展起到重要的推动作用。咒语与主人公的性格、行为以及内心活动、命运走向息息相关,并最终导致麦克白命运悲剧的发生。集众恶于一身的女巫是咒语现象的主体,艰深晦涩、言辞激烈的诗体是咒语的具体表现形式,咒语的预言性质笼罩全篇,影响着人物的内心恶念,推动剧情发展,成为贯穿全剧始终的主题线索。     

A New Methodology for Before–After Safety Assessment Using Survival Analysis and Longitudinal Data

The widely used empirical Bayes (EB) and full Bayes (FB) methods for before–after safety assessment are sometimes limited because of the extensive data needs from additional reference sites. To address this issue, this study proposes a novel before–after safety evaluation methodology based on survival analysis and longitudinal data as an alternative to the EB/FB method. A Bayesian survival analysis (SARE) model with a random effect term to address the unobserved heterogeneity across sites is developed. The proposed survival analysis method is validated through a simulation study before its application. Subsequently, the SARE model is developed in a case study to evaluate the safety effectiveness of a recent red‐light‐running photo enforcement program in New Jersey. As demonstrated in the simulation and the case study, the survival analysis can provide valid estimates using only data from treated sites, and thus its results will not be affected by the selection of defective or insufficient reference sites. In addition, the proposed approach can take into account the censored data generated due to the transition from the before period to the after period, which has not been previously explored in the literature. Using individual crashes as units of analysis, survival analysis can incorporate longitudinal covariates such as the traffic volume and weather variation, and thus can explicitly account for the potential temporal heterogeneity.     

Challenges to Connecting Sociology and Service Learning

Service-learning programs are not free from challenges brought about by lack of financial support, lack of widespread commitment from professors, community agencies, and recipients of service, and lack of knowledge and insight in students directly involved in such programs. While service-learning initiatives and programs serve positive functions for organizations and individuals, rhetorical accolades for service learning can distort or omit the realities of program implementation and sustained delivery. This paper specifically explores the following challenges connected to service-learning programs: (1) pedagogical difficulties; (2) student limitations; (3) time constraints; and (4) community cooperation.     

Studying the Effects of the Audience on Verbal Behavior

The Analysis of Verbal Behavior -     

Non-ignorable missing covariate data in survival analysis: a case-study of an International Breast Cancer Study Group trial

Summary.  Non-ignorable missing data, a serious problem in both clinical trials and observational studies, can lead to biased inferences. Quality-of-life measures have become increasingly popular in clinical trials. However, these measures are often incompletely observed, and investigators may suspect that missing quality-of-life data are likely to be non-ignorable. Although several recent references have addressed missing covariates in survival analysis, they all required the assumption that missingness is at random or that all covariates are discrete. We present a method for estimating the parameters in the Cox proportional hazards model when missing covariates may be non-ignorable and continuous or discrete. Our method is useful in reducing the bias and improving efficiency in the presence of missing data. The methodology clearly specifies assumptions about the missing data mechanism and, through sensitivity analysis, helps investigators to understand the potential effect of missing data on study results.     

裴迪考论

裴迪是和王维同时而稍后的田园诗人 ,他的一生中大概有 2 0年是跟随着王维度过的。裴迪在唐代并不是显赫的诗人。但是他与当时除了李白以外的其他大诗人都有或多或少的联系。考证他的事迹和与这些诗人的关系 ,也可以使这些诗人得到更多的还原以被人们了解。