A new test for multivariate normality by combining extreme and nonextreme BHEP tests

In this article, we propose a new multiple test procedure for assessing multivariate normality, which combines BHEP (Baringhaus–Henze–Epps–Pulley) tests by considering extreme and nonextreme choices of the tuning parameter in the definition of the BHEP test statistic. Monte Carlo power comparisons indicate that the new test presents a reasonable power against a wide range of alternative distributions, showing itself to be competitive against the most recommended procedures for testing a multivariate hypothesis of normality. We further illustrate the use of the new test for the Fisher Iris dataset.     

Feminist power and its implications on Uganda’s malaria communication campaign

This paper examines power and its manifestation in Uganda’s “Stop Malaria Campaign.” It specifically questions the apparent radical feminism, which is conceptualized as a quest for power, and how such excesses drive implementation of the campaign. The paper explains data collected through focus group discussions and key informant interviews using feminist communication theory as informed by the critical ideas of feminism and power. These three ideas help to put into perspective: domination of the campaign by one gender, interpretation of the campaign’s objectives to suit that one gender, and communication methods used in the campaign. Analysis of the above three processes shows that men are the weaker gender in the malaria prevention drive, an idea that has clashed with the existing male chauvinism on which several families still thrive in Africa. A view that radical feminism should be seen as an organized form of power that needs to be checked if Uganda’s malaria communication campaign is to be implemented successfully is herein proposed, along with some solutions to the challenges.     

争国本：君臣博弈的政治解读

万历年间册立太子之争被称为＂争国本＂,围绕册立皇长子朱常洛还是皇三子朱常洵,明神宗万历与廷臣进行了旷日持久的博弈。整个事件由廷臣温和的建议开始,经过长期而激烈的斗争,以至于谣言四起,最后借助太后的力量得以解决,按祖制皇长子朱常洵被册立为太子,皇三子朱常洛受封福王。争国本是认识明朝政治运作的典型样本,折射了专制王朝政治运作的内在逻辑。     

A latent variable model for analyzing mixed longitudinal (k,l)-inflated count and ordinal responses

A random effects model for analyzing mixed longitudinal count and ordinal data is presented where the count response is inflated in two points (k and l) and an (k,l)-Inflated Power series distribution is used as its distribution. A full likelihood-based approach is used to obtain maximum likelihood estimates of parameters of the model. For data with non-ignorable missing values models with probit model for missing mechanism are used.The dependence between longitudinal sequences of responses and inflation parameters are investigated using a random effects approach. Also, to investigate the correlation between mixed ordinal and count responses of each individuals at each time, a shared random effect is used. In order to assess the performance of the model, a simulation study is performed for a case that the count response has (k,l)-Inflated Binomial distribution. Performance comparisons of count-ordinal random effect model, Zero-Inflated ordinal random effects model and (k,l)-Inflated ordinal random effects model are also given. The model is applied to a real social data set from the first two waves of the national longitudinal study of adolescent to adult health (Add Health study). In this data set, the joint responses are the number of days in a month that each individual smoked as the count response and the general health condition of each individual as the ordinal response. For the count response there is incidence of excess values of 0 and 30.     

Confidence interval estimation and hypothesis testing for a common correlation coefficient

Several procedures have been proposed for testing the hypothesis that all off-diagonal elements of the correlation matrix of a multivariate normal distribution are equal. If the hypothesis of equal correlation can be accepted, it is then of interest to estimate and perhaps test hypotheses for the common correlation. In this paper, two versions of five different test statistics are compared via simulation in terms of adequacy of the normal approximation, coverage probabilities of confidence intervals, control of Type I error, and power. The results indicate that two test statistics based on the average of the Fisher z-transforms of the sample correlations should be used in most cases. A statistic based on the sample eigenvalues also gives reasonable results for confidence intervals and lower-tailed tests.     

中华武术散打之局部力量与整体力量解读

散打之力量是散打运动中除运动技术等要素外,非常重要的另一要素,散打之力量在运动中表现出两个方面的应用,即散打之局部力量和整体力量;散打之局部力量和整体力量在比赛中交替展现,正是由于散打之局部力量和整体力量的不停变换使用及不同情况下各种力量共同作用,运动员才能在比赛中赢得胜利。散打之局部力量与整体力量的科学应用与训练不仅塑造了练习者完美的运动身形,而且培养了个人不凡的运动气质,是一项完美的体育运动。     

论成品油定价机制中的有限规制：基于合谋的视角

利用单期静态博弈分析法、有限期动态博弈分析法和无限期动态博弈分析法对成品油定价机制中寡头厂商的合谋行为进行了分析。研究发现：两家寡头厂商在合谋条件下的收益均高于双方各自独立定产条件下的收益，因此，双方存在进行价格合谋的利益激励。基于此，我国成品油价格形成机制的改革可以考虑采用有限规制等手段。     

Comparing diagnostic tests: test of hypothesis for likelihood ratios

Likelihood ratios (LRs) are used to characterize the efficiency of diagnostic tests. In this paper, we use the classical weighted least squares (CWLS) test procedure, which was originally used for testing the homogeneity of relative risks, for comparing the LRs of two or more binary diagnostic tests. We compare the performance of this method with the relative diagnostic likelihood ratio (rDLR) method and the diagnostic likelihood ratio regression (DLRReg) approach in terms of size and power, and we observe that the performances of CWLS and rDLR are the same when used to compare two diagnostic tests, while DLRReg method has higher type I error rates and powers. We also examine the performances of the CWLS and DLRReg methods for comparing three diagnostic tests in various sample size and prevalence combinations. On the basis of Monte Carlo simulations, we conclude that all of the tests are generally conservative and have low power, especially in settings of small sample size and low prevalence.     

Community Resilience and Decision Theory Challenges for Catastrophic Events

Extreme and catastrophic events pose challenges for normative models of risk management decision making. They invite development of new methods and principles to complement existing normative decision and risk analysis. Because such events are rare, it is difficult to learn about them from experience. They can prompt both too little concern before the fact, and too much after. Emotionally charged and vivid outcomes promote probability neglect and distort risk perceptions. Aversion to acting on uncertain probabilities saps precautionary action; moral hazard distorts incentives to take care; imperfect learning and social adaptation (e.g., herd‐following, group‐think) complicate forecasting and coordination of individual behaviors and undermine prediction, preparation, and insurance of catastrophic events. Such difficulties raise substantial challenges for normative decision theories prescribing how catastrophe risks should be managed. This article summarizes challenges for catastrophic hazards with uncertain or unpredictable frequencies and severities, hard‐to‐envision and incompletely described decision alternatives and consequences, and individual responses that influence each other. Conceptual models and examples clarify where and why new methods are needed to complement traditional normative decision theories for individuals and groups. For example, prospective and retrospective preferences for risk management alternatives may conflict; procedures for combining individual beliefs or preferences can produce collective decisions that no one favors; and individual choices or behaviors in preparing for possible disasters may have no equilibrium. Recent ideas for building “disaster‐resilient” communities can complement traditional normative decision theories, helping to meet the practical need for better ways to manage risks of extreme and catastrophic events.     

Monte Carlo comparison of five exponentiality tests using different entropy estimates

The paper studies five entropy tests of exponentiality using five statistics based on different entropy estimates. Critical values for various sample sizes determined by means of Monte Carlo simulations are presented for each of the test statistics. By simulation, we compare the power of these five tests for various alternatives and sample sizes.