Servant Leadership in the Public Sector: Employee Perspective

Public Organization Review - The purpose of this study is to explore how servant leadership affects public sector employee engagement, organisational ethical climate, and public sector reform, of...     

食管癌患者健康相关生命质量研究

目的:探讨食管癌患者的健康相关生命质量现状及影响因素?方法:采用一般资料问卷?欧洲五维度健康评定量表(EQ-5D量表),对209例食管癌患者进行问卷调查,采用单因素分析和多因素分析探讨食管癌患者健康相关生命质量的影响因素? 结果:食管癌患者行动?自我照顾?日常活动?疼痛/不适?焦虑/抑郁五个维度存在问题的比例分别为18.2%?12.0%?22.0%?38.3%?25.4%;自评健康得分(VAS评分)为(75.20 ± 11.00)分;综合健康指数得分(Index得分)为(0.84 ± 0.22)分?患者的性别?家庭年收入?文化程度是VAS评分的主要影响因素;患者的年龄?治疗方式?肿瘤分期?医保类型是Index得分的主要影响因素?结论:实施心理干预?早诊早治?大病医疗保险有助于提高食管癌患者健康相关生命质量?     

农户苜蓿种植规模效率的实证分析---基于河北省黄骅市的实证分析

种植苜蓿对于畜牧业发展、土地资源改善具有重要意义,发展苜蓿种植是2015年中央一号文件的重要内容。本文以农户这一我国苜蓿种植主体为研究对象,利用河北省黄骅市的农户苜蓿种植调查数据,构建DEA模型对农户的苜蓿种植规模效率进行实证研究。结果表明,农户苜蓿种植获得最优效率的规模为18亩左右。利用Tobit模型,对影响规模效率的因素进一步分析计算发现,调查区域农户苜蓿种植处于粗放阶段,应鼓励发展苜蓿专业种植户,在种子、技术、资金及机械补贴、种植补贴等方面给予支持。     

"一带一路"沿线国家语言政策概述

"一带一路"沿线有大约65个国家,53种官方语言,语言使用情况复杂.沿线国家重视语言问题,注重国家层面的语言规划,大多在宪法中都有与语言相关的条款.大多数沿线国家都比较关注宏观层面的语言规划,通过显性的语言政策处理主体民族语言、少数民族语言和外语的相互关系及其使用.沿线国家语言使用及语言政策呈现出鲜明的区域特色.文章也提出一些思考,以期为我国制定和实施面向"一带一路"的语言战略提供参考.     

社会组织与政府协同的进化博弈分析

社会组织作为协同治理多元化主体中的重要一员,在协同治理中发挥着不可替代的作用,但为何在社会组织协同政府治理已成共识的前提下双方协同尚处于低水平现状,现有研究缺乏解释力.本文运用进化博弈论理论,构建社会组织与政府协同的非对称进化博弈模型,从理论上分析判定影响双方协同策略选择的关键因素.研究表明:协同成本与协同额外收益的分配直接影响社会组织与政府协同策略的选择.因此,要推进我国社会组织与政府协同关系的深入,应充分发挥政府部门在协同中的主导作用、不断降低协同所产生的成本并优化协同额外收益的分配.     

中国经济结构再平衡与长期增长

在经济新常态下,中国经济由原来的高速增长转向追求中高速和质量型的增长,这是中国经济转型与产业升级的必然选择。解决中国经济突出的结构性问题,实现经济结构转型与产业升级,也就是经济结构再平衡,使经济增长由主要依赖规模扩张转向主要依赖技术进步,是中国经济长期可持续增长的保障,也是中国多年来致力的发展与改革目标,是一项需要长期努力的任务。经济结构再平衡有赖于经济长期发展的支持;经济长期发展和增长周期延长,才能为经济转型与升级的结构再平衡提供时间、空间的回旋。我们要紧紧抓住国家新型城镇化战略和“一带一路”战略的实施契机,按照“四个全面”战略布局的要求,支持民营企业参与中国经济的空间结构再平衡,以全面依法治国推进中国经济结构的再平衡和长期的经济增长。     

A win ratio approach to comparing continuous non‐normal outcomes in clinical trials

Clinical trials are often designed to compare continuous non‐normal outcomes. The conventional statistical method for such a comparison is a non‐parametric Mann–Whitney test, which provides a P‐value for testing the hypothesis that the distributions of both treatment groups are identical, but does not provide a simple and straightforward estimate of treatment effect. For that, Hodges and Lehmann proposed estimating the shift parameter between two populations and its confidence interval (CI). However, such a shift parameter does not have a straightforward interpretation, and its CI contains zero in some cases when Mann–Whitney test produces a significant result. To overcome the aforementioned problems, we introduce the use of the win ratio for analysing such data. Patients in the new and control treatment are formed into all possible pairs. For each pair, the new treatment patient is labelled a ‘winner’ or a ‘loser’ if it is known who had the more favourable outcome. The win ratio is the total number of winners divided by the total numbers of losers. A 95% CI for the win ratio can be obtained using the bootstrap method. Statistical properties of the win ratio statistic are investigated using two real trial data sets and six simulation studies. Results show that the win ratio method has about the same power as the Mann–Whitney method. We recommend the use of the win ratio method for estimating the treatment effect (and CI) and the Mann–Whitney method for calculating the P‐value for comparing continuous non‐Normal outcomes when the amount of tied pairs is small. Copyright © 2016 John Wiley & Sons, Ltd.     

Modelling PK/QT relationships from Phase I dose‐escalation trials for drug combinations and developing quantitative risk assessments of clinically relevant QT prolongations

In current industry practice, it is difficult to assess QT effects at potential therapeutic doses based on Phase I dose‐escalation trials in oncology due to data scarcity, particularly in combinations trials. In this paper, we propose to use dose‐concentration and concentration‐QT models jointly to model the exposures and effects of multiple drugs in combination. The fitted models then can be used to make early predictions for QT prolongation to aid choosing recommended dose combinations for further investigation. The models consider potential correlation between concentrations of test drugs and potential drug–drug interactions at PK and QT levels. In addition, this approach allows for the assessment of the probability of QT prolongation exceeding given thresholds of clinical significance. The performance of this approach was examined via simulation under practical scenarios for dose‐escalation trials for a combination of two drugs. The simulation results show that invaluable information of QT effects at therapeutic dose combinations can be gained by the proposed approaches. Early detection of dose combinations with substantial QT prolongation is evaluated effectively through the CIs of the predicted peak QT prolongation at each dose combination. Furthermore, the probability of QT prolongation exceeding a certain threshold is also computed to support early detection of safety signals while accounting for uncertainty associated with data from Phase I studies. While the prediction of QT effects is sensitive to the dose escalation process, the sensitivity and limited sample size should be considered when providing support to the decision‐making process for further developing certain dose combinations. Copyright © 2016 John Wiley & Sons, Ltd.     

Model averaging inconcentration–QT analyses

This article describes how a frequentist model averaging approach can be used for concentration–QT analyses in the context of thorough QTc studies. Based on simulations, we have concluded that starting from three candidate model families (linear, exponential, and Emax) the model averaging approach leads to treatment effect estimates that are quite robust with respect to the control of the type I error in nearly all simulated scenarios; in particular, with the model averaging approach, the type I error appears less sensitive to model misspecification than the widely used linear model. We noticed also few differences in terms of performance between the model averaging approach and the more classical model selection approach, but we believe that, despite both can be recommended in practice, the model averaging approach can be more appealing because of some deficiencies of model selection approach pointed out in the literature. We think that a model averaging or model selection approach should be systematically considered for conducting concentration–QT analyses. Copyright © 2016 John Wiley & Sons, Ltd.     

权力话语视阈下的《愤怒的葡萄》

《愤怒的葡萄》是约翰·斯坦贝克的代表作。小说讲述了在20世纪30年代美国经济萧条背景下,乔德一家人向加利福尼亚逃荒,以图获得美好的生活。然而,现实的残酷造成等待他们的仍然是饥荒、贫穷和失业,美梦的破碎导致成千上万像乔德这样的家庭奋起反抗。以权力话语理论为切入点,对小说中的主要人物进行解读,有助于实现微观权力和宏观权力的结合,进一步加深对小说的理解。