隐喻的语篇性分析

隐喻是人类认知思维的语言表现。隐喻是话语现象。其语篇性表现为衔接与连贯、信息性、目的性等因素。衔接与连贯是语篇的基础；隐喻的信息性蕴涵其目的性，同时受到目的性的影响；目的性实现语篇的真实意图。     

The evaluation of DNA evidence in pedigrees requiring population inference

Summary. The evaluation of nuclear DNA evidence for identification purposes is performed here taking account of the uncertainty about population parameters. Graphical models are used to detail the hypotheses being debated in a trial with the aim of obtaining a directed acyclic graph. Graphs also clarify the set of evidence that contributes to population inferences and they also describe the conditional independence structure of DNA evidence. Numerical illustrations are provided by re-examining three case-studies taken from the literature. Our calculations of the weight of evidence differ from those given by the authors of case-studies in that they reveal more conservative values.     

Issues in applying recent CPMP ‘Points to Consider’ and FDA guidance documents with biostatistical implications

The International Conference on Harmonisation guideline ‘Statistical Principles for Clinical Trials’ was adopted by the Committee for Proprietary Medicinal Products (CPMP) in March 1998, and consequently is operational in Europe. Since then more detailed guidance on selected topics has been issued by the CPMP in the form of ‘Points to Consider’ documents. The intent of these was to give guidance particularly to non‐statistical reviewers within regulatory authorities, although of course they also provide a good source of information for pharmaceutical industry statisticians. In addition, the Food and Drug Administration has recently issued a draft guideline on data monitoring committees. In November 2002 a one‐day discussion forum was held in London by Statisticians in the Pharmaceutical Industry (PSI). The aim of the meeting was to discuss how statisticians were responding to some of the issues covered in these new guidelines, and to document consensus views where they existed. The forum was attended by industry, academic and regulatory statisticians. This paper outlines the questions raised, resulting discussions and consensus views reached. It is clear from the guidelines and discussions at the workshop that the statistical analysis strategy must be planned during the design phase of a clinical trial and carefully documented. Once the study is complete the analysis strategy should be thoughtfully executed and the findings reported. Copyright © 2003 John Wiley & Sons, Ltd.     

浅谈高速公路公司财务预警系统

文章论述了利用财务指标分析法及判别分析法 ,对高速公路公司财务危机进行预测和警报 ,并运用多元判别分析法推导出高速公路行业的财务预警模型     

高等教育私营化问题及其对中国的启示

对高等教育私营化这一国际化趋势进行初步探索,分析高等教育私营化带来的利与弊。结合我国高等教育的现状,探讨如何应对高等教育私营化问题及其对中国的启示。     

Economic Determinants of Net International Migration in Western Europe

This paper aims to estimate theinfluence of economic determinants on netinternational migration in Western Europe inthe period 1960–1998. Net migration rates(i.e., population growth minus natural increase,divided by the midyear population) constitutethe dependent variable. The economicdeterminants used in this study are GDP percapita, unemployment, and average educationallevel (amount of human capital) of thepopulation. Time series regression models havebeen used in country-specific analyses. Inaddition, a pooled cross-sectional time seriesanalysis has been made. The analyses suggestthat GDP per capita has a positive effect andunemployment a negative effect on a country'snet international migration.     

Three-level main-effects designs exploiting prior information about model uncertainty

To explore the projection efficiency of a design, Tsai, et al [2000. Projective three-level main effects designs robust to model uncertainty. Biometrika 87, 467–475] introduced the Q criterion to compare three-level main-effects designs for quantitative factors that allow the consideration of interactions in addition to main effects. In this paper, we extend their method and focus on the case in which experimenters have some prior knowledge, in advance of running the experiment, about the probabilities of effects being non-negligible. A criterion which incorporates experimenters’ prior beliefs about the importance of each effect is introduced to compare orthogonal, or nearly orthogonal, main effects designs with robustness to interactions as a secondary consideration. We show that this criterion, exploiting prior information about model uncertainty, can lead to more appropriate designs reflecting experimenters’ prior beliefs.     

Predictive Bayesian Microbial Dose-Response Assessment Based on Suggested Self-Organization in Primary Illness Response: Cryptosporidium parvum

The probability of illness caused by very low doses of pathogens cannot generally be tested due to the numbers of subjects that would be needed, though such assessments of illness dose response are needed to evaluate drinking water standards. A predictive Bayesian dose-response assessment method was proposed previously to assess the unconditional probability of illness from available information and avoid the inconsistencies of confidence-based approaches. However, the method uses knowledge of the conditional dose-response form, and this form is not well established for the illness endpoint. A conditional parametric dose-response function for gastroenteric illness is proposed here based on simple numerical models of self-organized host-pathogen systems and probabilistic arguments. In the models, illnesses terminate when the host evolves by processes of natural selection to a self-organized critical value of wellness. A generalized beta-Poisson illness dose-response form emerges for the population as a whole. Use of this form is demonstrated in a predictive Bayesian dose-response assessment for cryptosporidiosis. Results suggest that a maximum allowable dose of 5.0 x 10(-7) oocysts/exposure (e.g., 2.5 x 10(-7) oocysts/L water) would correspond with the original goals of the U.S. Environmental Protection Agency Surface Water Treatment Rule, considering only primary illnesses resulting from Poisson-distributed pathogen counts. This estimate should be revised to account for non-Poisson distributions of Cryptosporidium parvum in drinking water and total response, considering secondary illness propagation in the population.     

Causal Reasoning from Longitudinal Data*

Abstract. This paper reviews some of the key statistical ideas that are encountered when trying to find empirical support to causal interpretations and conclusions, by applying statistical methods on experimental or observational longitudinal data. In such data, typically a collection of individuals are followed over time, then each one has registered a sequence of covariate measurements along with values of control variables that in the analysis are to be interpreted as causes, and finally the individual outcomes or responses are reported. Particular attention is given to the potentially important problem of confounding. We provide conditions under which, at least in principle, unconfounded estimation of the causal effects can be accomplished. Our approach for dealing with causal problems is entirely probabilistic, and we apply Bayesian ideas and techniques to deal with the corresponding statistical inference. In particular, we use the general framework of marked point processes for setting up the probability models, and consider posterior predictive distributions as providing the natural summary measures for assessing the causal effects. We also draw connections to relevant recent work in this area, notably to Judea Pearl's formulations based on graphical models and his calculus of so‐called do‐probabilities. Two examples illustrating different aspects of causal reasoning are discussed in detail.     

Consistencies and Inconsistencies: Mental Health, Compulsory Treatment and Community Capacity Building in England, Wales and Australia

In relation to mental health, it is clear that medicalized underpinnings,the provision of a clinically orientated evidence base for practiceand the need to contain ‘risk’ continue to be prioritized,particularly when compulsory intervention is considered. Thisis despite the increasing influence of a citizenship and socialjustice agenda which is being promoted by psychiatrists involvedin the development of ‘postpsychiatry’, as wellas by service users/survivors. These drivers are not mutuallyexclusive, but in the context of compulsory treatment, thereare clear tensions. In this article, the policy surroundingmental health and compulsory intervention in Australia and inEngland and Wales is explored. In the context of this discussion,three ways in which current government policy can be interpretedare examined and links made between these interpretations anddifferent ways of viewing the relationship between mental healthand community capacity building. With regard to social workpractice, it is argued that a response to mental ill healthwhich concentrates on an individualized ‘diagnose andtreat’ approach, which particularly comes to the foreat times of compulsory intervention, has limited capacity tofacilitate community engagement, foster social inclusion andgenerate reciprocal dynamics between positive mental healthand community capacity building.