Research and Practice:

In this multiply-authored account, five academicians discuss the connections between their work as clinicians and their clinical qualitative research. Each saw connections between practice and research, and each in her or his own domain of interest has found that practice informs research and research informs practice. This article also introduces three major types of qualitative clinical family research: conversational analysis, recursive frame analysis, and hermeneutic phenomenology.     

Goodness-of-Fit Tests for Multiplicative Models with Dependent Data

Abstract.  Several classical time series models can be written as a regression model between the components of a strictly stationary bivariate process. Some of those models, such as the ARCH models, share the property of proportionality of the regression function and the scale function, which is an interesting feature in econometric and financial models. In this article, we present a procedure to test for this feature in a non-parametric context. The test is based on the difference between two non-parametric estimators of the distribution of the regression error. Asymptotic results are proved and some simulations are shown in the paper in order to illustrate the finite sample properties of the procedure.     

基于主成分分析法的自主创新能力综合评价——以湖南省为例

自主创新是中国实现现代化的关键。通过利用主成分分析法对湖南自主创新能力进行综合评价,结果显示湖南自主创新能力呈现出逐步提高的趋势,但和较发达的省份相比,仍存在较大差距。因此,湖南省应进一步增加研发和教育投入,加强人才的引进和培养,通过自主创新提升湖南的发展力和竞争力。     

传统统计面对的挑战

针对统计的黑匣子特性,借用Breiman的两种统计文化的平台,分析传统统计面临的挑战和危机,并探索统计领域究竟要向何处发展的问题。研究表明：统计学必须重新回到针对实际问题而与数据打交道,并且创造有关理论的传统上来。只有这样,才能应对不断产生的新问题所带来的挑战。     

Biased Bootstrap Methods for Reducing the Effects of Contamination

Contamination of a sampled distribution, for example by a heavy-tailed distribution, can degrade the performance of a statistical estimator. We suggest a general approach to alleviating this problem, using a version of the weighted bootstrap. The idea is to 'tilt' away from the contaminated distribution by a given (but arbitrary) amount, in a direction that minimizes a measure of the new distribution's dispersion. This theoretical proposal has a simple empirical version, which results in each data value being assigned a weight according to an assessment of its influence on dispersion. Importantly, distance can be measured directly in terms of the likely level of contamination, without reference to an empirical measure of scale. This makes the procedure particularly attractive for use in multivariate problems. It has several forms, depending on the definitions taken for dispersion and for distance between distributions. Examples of dispersion measures include variance and generalizations based on high order moments. Practicable measures of the distance between distributions may be based on power divergence, which includes Hellinger and Kullback–Leibler distances. The resulting location estimator has a smooth, redescending influence curve and appears to avoid computational difficulties that are typically associated with redescending estimators. Its breakdown point can be located at any desired value ε∈ (0, ½) simply by 'trimming' to a known distance (depending only on ε and the choice of distance measure) from the empirical distribution. The estimator has an affine equivariant multivariate form. Further, the general method is applicable to a range of statistical problems, including regression.     

The Effect of Drop-Out on the Efficiency of Longitudinal Experiments

It is shown that drop-out often reduces the efficiency of longitudinal experiments considerably. In the framework of linear mixed models, a general, computationally simple method is provided, for designing longitudinal studies when drop-out is to be expected, such that there is little risk of large losses of efficiency due to the missing data. All the results are extensively illustrated using data from a randomized experiment with rats.     

An experiment in primary health care provision

Missing data and, more generally, imperfections in implementing a study design are an endemic problem in large scale studies involving human subjects. We present an analysis of an experiment in the interaction between general practitioners and their patients, in which the issue of missing data is addressed by a sensitivity analysis using multiple imputation. Instead of specifying a model for missingness we explore certain extreme ways of departing from the assumption of data missing at random and establish the largest extent of such departures which would still fail to supplant the evidence about the studied effect. An important advantage of the approach is that the algorithm intended for the complete data, to fit generalized linear models with random effects, is used without any alteration.     

从数据垄断走向数据开放：数据成为必需设施的竞争法分析

数字经济下,数据发挥着越来越重要的作用,而拥有大量数据的支配企业却往往拒绝其他经营者对数据的访问,意图垄断数据资源。竞争法有必要通过必需设施规则,对支配企业拒绝访问的行为予以规制,实现数据开放,促进数据资源的流通、利用。结合必需设施规则的发展历程,必需设施规则在数字经济背景下的适用需要有严格的条件限制。这些条件包括:在经营者具有市场支配地位的前提条件下,首先数据需要构成必需设施,即数据是经营者参与市场竞争所必不可少的;其次,支配企业拒绝数据访问的行为所产生的消极效果明显大于积极效果;最后,支配企业拒绝数据访问不存在合理的理由。满足了上述条件后,支配企业才需要承担允许数据访问的义务。在此基础上,竞争法需要针对数据访问的具体要求以及其可能与个人数据保护法、知识产权法之间的关系进行细化,以使数据访问在实践中更具有操作性。具体而言,竞争法对数据访问的要求主要有三点:其一,其他经营者对数据的访问应当是公平的;其二,其他经营者对数据的访问应当是现实可行的;其三,其他经营者对数据进行访问需要支付合理的费用。在竞争法与个人数据保护法之间的关系上,一方面,个人数据保护法在一定程度上阻碍了其他经营者对数据的访问;另一方面,个人数据保护法与竞争法在价值上存在着统一性。在竞争法与知识产权法之间的关系上,大多数情况下,支配企业拒绝其他经营者对受到知识产权保护的数据的访问的行为是合法的,但是支配企业也需注意在合理的范围内行使权利,不得滥用知识产权限制数据访问的实施。在数字经济时代,我国有必要在反垄断法规范体系中纳入必需设施规则,同时在相关的法律规范和指南中对数据访问的具体内容进行设计,加强与个人数据保护、知识产权等相关法律规范的协调,实现数据访问的本土化建构,促进市场竞争,挖掘数据的巨大价值。     

Chinese and Americans Agree on What Is Fair,but Disagree on What Is Best in Societal Decisions Affecting Health and Safety Risks

Through surveys of students and junior professionals and interviews with business and government executives, we studied Chinese choices and fairness perceptions in risky health and safety decisions. The survey responses were compared with American responses from an earlier study by Keller and Sarin.The survey results show that the American and Chinese respondents had similar fairness perceptions, but the Chinese did not make decisions that were consistent with their fairness perceptions, whereas the Americans did. We found that the middle-age Chinese professionals tended to make choices that were more different from the Americans than were the choices of the young Chinese management students. It is likely that these discrepancies were caused by cultural differences, with the younger Chinese tending to face a stronger Western influence.The insights from the survey results were enriched by interviews that revealed fairness perceptions of Chinese business and government executives. A framework to interpret cultural influences on decision making was also proposed.     

实验室工作定量评价

针对实验室工作各指标量纲不统一,较难定量度量的情况.笔者力图采用集对分析,给定一指标优值,将被评人员各指标连同其量纲与指标优值直接比较定量评价,以合理、全面反映实验室工作的质与量.使分配更能体现多劳多得的原则,进一步词动实验室人员的工作积极性.