文化自觉：照亮中国基础教育理性化阴影之灯

中国传统基础教育以私塾为形式,人文性的四书五经为其内容。清末民初,私塾为理性化的班级授课制所取代,这是理性在教育领域的第一次胜利;近十年来,基础教育集中于乡镇以上学校,村小学被拆并,乡镇初中日渐缩减,农村教育资源被抽空,这是理性在教育领域的进一步扩张。理性化带有形式合理而实质不合理的悖论特质。基础教育之理性化带来高效益的同时,也导致文化意识与价值观念越来越淡漠。目前,较为富强的中国社会也越发意识到,文化归宿之于中国人安身立命以及社会的可持续发展的价值所在。克服教育理性化阴影,在于文化的再植入。故而,面对教育理性化,亟待嵌入文化意识,须将本土文化嵌入基础教育之中以避免教育的无根性。     

旅游资源规模化开发与农牧民生计方式转换——基于西藏“国际旅游小镇”的案例研究

作为对口援藏项目中规模最大的项目,鲁朗国际旅游小镇项目总投资超过30亿元,必然会对项目所在地鲁朗镇居民的生计方式带来巨大的影响.本文分析了当地居民的生计方式从自给自足的农牧业以及狩猎采集到伐木经济再到家庭旅馆的变迁过程,在旅游资源规模化开发下,农牧民生计方式发生非常大的转换,也对当地农牧民生计产生了负面冲击,为此,政府采取了保护性措施.作者发现,由于政府与当地农牧民所占视角的不同,在一些政策实施上,当地政府的实施愿望与当地农牧民想法产生了差异,故当地农牧民并不完全认同政府推行的一些政策.     

借势发展:县域经济科学发展的“快车道”

主动就近承接先进地区的产业转移和要素外溢,借梯登高、借势发展,是县域经济又好又快发展的重要途径.高密市借鉴江苏省昆山市借势上海发展的模式与经验,立足实际、明确思路;主动作为、全面对接;突出重点、创新举措,"主动对接、率先融入" 青岛城市群,实现了思想观念、行政机制、经济结构、基础设施、科技与人才、信息资源、产业链条等的全方位对接,发展配套产业和"配角"经济,促进了区域经济的持续、快速发展.     

加强医学伦理素养教育的机制、途径和方法

提高医学伦理素养有利于构建和谐的医惠关系,而和谐的医患关系是和谐社会的重要组成部分。从医学院校、医院和社会三个方面探讨增强医学伦理素养的机制、途径与方法,很有意义。     

Finite normal mixture copulas for multivariate discrete data modeling

A new family of copulas is introduced that provides flexible dependence structure while being tractable and simple to use for multivariate discrete data modeling. The construction exploits finite mixtures of uncorrelated normal distributions. Accordingly, the cumulative distribution function is simply the product of univariate normal distributions. At the same time, however, the mixing operation introduces association. The properties of the new family of copulas are examined and a concrete application is used to show its applicability.     

Comparison of dichotomized and distributional approaches in rare event clinical trial design: a fixed Bayesian design

This research was motivated by our goal to design an efficient clinical trial to compare two doses of docosahexaenoic acid supplementation for reducing the rate of earliest preterm births (ePTB) and/or preterm births (PTB). Dichotomizing continuous gestational age (GA) data using a classic binomial distribution will result in a loss of information and reduced power. A distributional approach is an improved strategy to retain statistical power from the continuous distribution. However, appropriate distributions that fit the data properly, particularly in the tails, must be chosen, especially when the data are skewed. A recent study proposed a skew-normal method. We propose a three-component normal mixture model and introduce separate treatment effects at different components of GA. We evaluate operating characteristics of mixture model, beta-binomial model, and skew-normal model through simulation. We also apply these three methods to data from two completed clinical trials from the USA and Australia. Finite mixture models are shown to have favorable properties in PTB analysis but minimal benefit for ePTB analysis. Normal models on log-transformed data have the largest bias. Therefore we recommend finite mixture model for PTB study. Either finite mixture model or beta-binomial model is acceptable for ePTB study.     

A new generalized two-sided class of distributions with an emphasis on two-sided generalized normal distribution

The ordinary-G class of distributions is defined to have the cumulative distribution function (cdf) as the value of the cdf of the ordinary distribution F whose range is the unit interval at G, that is, F(G), and it generalizes the ordinary distribution. In this work, we consider the standard two-sided power distribution to define other classes like the beta-G and the Kumaraswamy-G classes. We extend the idea of two-sidedness to other ordinary distributions like normal. After studying the basic properties of the new class in general setting, we consider the two-sided generalized normal distribution with maximum likelihood estimation procedure.     

Bootstrap methods for multivariate hypothesis testing

The nonparametric and parametric bootstrap methods for multivariate hypothesis testing are developed. They are used to approximate the null distribution of the test statistics proposed by Duchesne and Francq (2015 Duchesne, P., Francq, C. (2015). Multivariate hypothesis testing using generalized and {2}-inverses—with applications. Statistics 49:475–496.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]), resulting in bootstrap testing procedures. In the problem of testing for the mean vector of a multivariate distribution, the asymptotic validity of the bootstrap methods is proved. The finite sample performance of the new solutions is demonstrated by means of Monte Carlo simulation studies. They indicate that for small-sample size, the bootstrap tests provide a better finite sample properties than the asymptotic tests considered by Duchesne and Francq (2015 Duchesne, P., Francq, C. (2015). Multivariate hypothesis testing using generalized and {2}-inverses—with applications. Statistics 49:475–496.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]).     

Bootstrap approach to test the homogeneity of order restricted mean vectors when the covariance matrices are unknown

Testing homogeneity of multivariate normal mean vectors under an order restriction when the covariance matrices are unknown, arbitrary positive definite and unequal are considered. This problem of testing has been studied to some extent, for example, by Kulatunga and Sasabuchi (1984 Kulatunga, D. D. S., Sasabuchi, S. (1984). A test of homogeneity of mean vectors against multivariate isotonic alternatives. Mem Fac Sci, Kyushu Univ Ser A Mathemat 38:151–161. [Google Scholar]) when the covariance matrices are known and also Sasabuchi et al. (2003 Sasabuchi, S., Tanaka, K., Tsukamodo, T. (2003). Testing homogeneity of multivariate normal mean vectors under an order restriction when the covariance matrices are common but unknown. Annals of Statistics. 31(5):1517–1536.[Web of Science ®] , [Google Scholar]) and Sasabuchi (2007 Sasabuchi, S. (2007). More powerful tests for homogeneity of multivariate normal mean vectors under an order restriction. Sankhya 69(4):700–716. [Google Scholar]) when the covariance matrices are unknown but common. In this paper, a test statistic is proposed and because of the main advantage of the bootstrap test is that it avoids the derivation of the complex null distribution analytically, a bootstrap test statistic is derived and since the proposed test statistic is location invariance the bootstrap p-value defined logical and some steps are presented to estimate it. Our numerical studies via Monte Carlo simulation show that the proposed bootstrap test can correctly control the type I error rates. The power of the test for some of the p-dimensional normal distributions is computed by Monte Carlo simulation. Also, the null distribution of test statistic is estimated using kernel density. Finally, the bootstrap test is illustrated using a real data.     

Likelihood procedure for testing changes in skew normal model with applications to stock returns

The skew normal distribution family is an attractive distribution family due to its mathematical tractability and inclusion of the normal distribution as the special case. It has wide applications in many applied fields such as finance, economics, and medical research. Such a distribution family has been studied extensively since it was introduced by Azzalini in 1985 Azzalini, A. (1985). A class of distributions which includes the normal ones. Scandinavian Journal of Statistics 12:171–178. [Google Scholar] for the first time. Yet, few work has been done on the study of change point problem related to this distribution family. In this article, we propose the likelihood ratio test (LRT) to detect changes in the parameters of the skew normal distribution associated with some asymptotic results of the test statistic. Simulations have been conducted under different scenarios to investigate the performance of the proposed method. Comparisons to some other existing method indicate the comparable power of the method in detecting changes in parameters of the skew normal distribution model. Applications on two real data: Brazilian and Tanzanian stock returns illustrate the detection procedure.