Two stage multiple comparison procedures based on the studentized range

Stein’s (1945) two sample approach and Tukey’s T-Method of multiple comparisons (see e.g. Miller, 1966, Ch. 2) are combined to obtain fixed width simultaneous confidence intervals and simultaneous test procedures of predetermined Type I and Type II error levels, for all contrasts, in a one way layout. The necessary constants for implementing the two stage procedure are obtained under a least favorable configuration of the parameters. This provides the required protection of the null and alternative hypotheses under any configuration of parameters. A table is provided for some selected designs and error levels and an example is given to illustrate certain features of the new procedure.     

Bayes Prediction for a Heteroscedastic Regression Superpopulation Model Using Balanced Loss Function

We consider Prais–Houthakker heteroscedastic normal regression model having variance of the dependent variable same as square of its expectation. Bayes predictors for the regression coefficient and the mean of a finite population are derived using Zellner's balanced loss function. Bayes predictive expected losses are obtained and compared with those of classical predictors and Bayes predictors under squared error loss function to examine their loss robustness.     

High-order extensions of the Double Chain Markov Model

The Double Chain Markov Model is a fully Markovian model for the representation of time-series in random environments. In this article, we show that it can handle transitions of high-order between both a set of observations and a set of hidden states. In order to reduce the number of parameters, each transition matrix can be replaced by a Mixture Transition Distribution model. We provide a complete derivation of the algorithms needed to compute the model. Three applications, the analysis of a sequence of DNA, the song of the wood pewee, and the behavior of young monkeys show that this model is of great interest for the representation of data that can be decomposed into a finite set of patterns.     

OBE理念下对高校微课教学价值的反思

作为教育信息化时代新技术与教育改革融合发展的共生产物,微课在教育领域备受关注。高校微课的快速发展对教师教学活动层面产生了一些影响,但对教学水平和人才培养质量的提升并没有产生实质性的助推力,且存在实践成效不够显著、系统的价值思考不够深入、对学生学习成效的关注不够充分、理论支撑体系不够成熟等不足之处。因此,在成果导向（Outcome-Based Education,OBE）理念下反思高校微课的目标定位、价值取向、教学设计和效果评价原则,应“以生为本”“以学为中心”,以提升学生综合能力为目标,以促进学生成功发展为取向,坚持成果导向反向设计原则及多元化、可迁移性的评价原则。     

医药企业负面网络舆情演化及应对策略研究

探讨因媒体不当报道引发医药企业网络舆情危机的演变规律,为企业找寻适宜的对策,有助于提高医药企业危机应对能力。文章以“深圳康泰公司乙肝疫苗信任危机”为例,构建了医药企业负面网络舆情演化和响应策略的系统动力学模型,并采用Vensim PLE软件进行仿真。结果表明:医药企业负面网络舆情经过酝酿、爆发、衰退三个阶段,且呈现爆发时间短、热度高、负面情绪强的特点;医药企业应根据舆情演化阶段特征采取不同应对策略,三个阶段对应有效应急策略依次是提升舆情监测能力、端正担责态度、提高信息公开度和沟通能力、注意形象修复和注重人文关怀。其中,提高信息公开度和沟通能力对负面网络舆情热度的峰值均有明显的削弱效果,整体提升企业舆情应对能力是改善舆情、挽救医药行业信任危机的有力措施。     

湖南省旅游生态安全动态评价及障碍因素分析

旅游生态安全是实现旅游地高质量发展、推进生态文明建设的重要环节。文章基于DPSIR模型构建湖南省旅游生态安全评价指标体系,运用熵权TOPSIS法对湖南省2011—2020年旅游生态安全进行动态评价,采用ArcGIS软件分析其空间演变特征,同时借助障碍度模型,揭示影响旅游生态安全的障碍因子。研究表明:(1)研究期内,湖南省旅游生态安全系数呈“小幅度下降,大幅度上升”的波浪形演化趋势。空间上呈现出由西北和东南向中心逐渐变好的分布格局。(2)游客密度、生活垃圾无害化处理率、工业固体废物综合利用率、GDP增长率、旅游经济密度等是主要障碍因子。     

差错管理氛围对员工建言行为的影响研究——基于链式中介作用模型

基于社会认知理论和社会交换理论,以320名具有5年以上工作经验的员工为调查对象,探讨了差错管理氛围如何促进员工建言行为的产生以及组织支持感和心理安全感在差错管理氛围与员工建言之间的链式中介作用。研究表明:差错管理氛围对员工建言行为具有显著的正向影响;组织支持感和心理安全感在差错管理氛围和员工建言行为之间起中介作用;组织支持感和心理安全感在差错管理氛围和员工建言行为之间起链式中介作用。因此,企业要努力营造积极的差错管理氛围,从而提高员工的组织支持感和心理安全感,促进员工建言行为的产生。     

Approximate MLEs of the parameters of location-scale models under type II censoring

Log-location-scale distributions are widely used parametric models that have fundamental importance in both parametric and semiparametric frameworks. The likelihood equations based on a Type II censored sample from location-scale distributions do not provide explicit solutions for the para-meters. Statistical software is widely available and is based on iterative methods (such as, Newton Raphson Algorithm, EM algorithm etc.), which require starting values near the global maximum. There are also many situations that the specialized software does not handle. This paper provides a method for determining explicit estimators for the location and scale parameters by approximating the likelihood function, where the method does not require any starting values. The performance of the proposed approximate method for the Weibull distribution and Log-Logistic distributions is compared with those based on iterative methods through the use of simulation studies for a wide range of sample size and Type II censoring schemes. Here we also examine the probability coverages of the pivotal quantities based on asymptotic normality. In addition, two examples are given.     

On constructing T 2 control charts for retrospective examination

In this paper we consider the issue of constructing retrospective T ² control chart limits so as to control the overall probability of a false alarm at a specified value. We describe an exact method for constructing the control limits for retrospective examination. We then consider Bonferroni-adjustments to Alt's control limit and to the standard x ² control limit as alternatives to the exact limit since it is computationally cumbersome to find the exact limit. We present the results of some simulation experiments that are carried out to compare the performance of these control limits. The results indicate that the Bonferroni-adjusted Alt's control limit performs better that the Bonferroni-adjusted x ² control limit. Furthermore, it appears that the Bonferroni-adjusted Alt's control limit is more than adequate for controlling the overall false alarm probability at a specified value.     

Der Sequentieile Quotiententest bei irreduziblen homogenen Markovschen Ketten mit endlichem Zustandsraum

The Sequential Probaility Ratio Test is applied to test two simple hypotheses about the transition probability matrix of an irreducible homogeneous MARKOV chain with finite state space. An analogue (14) of Wald's Fundamental Identity, the Operating Characteristic Function (20-21) and the Average Sample Number (22-23) are given. These statements are generalizations of the MARKOV chain as well as some more conditions about the eigenvalues of the transition probability matrix.