Pairwise comparisons of treatments with ordinal responses in a two-way setting

In clinical studies, pairwise comparisons are frequently performed to examine differences in efficacy between treatments. The statistical methods of pairwise comparisons are available when treatment responses are measured on an ordinal scale. The Wilcoxon–Mann–Whitney test and the latent normal model are popular examples. However, these procedures cannot be used to compare treatments in parallel groups (a two-way design) when overall type I error must be controlled. In this paper, we explore statistical approaches to the pairwise testing of treatments that satisfy the requirements of a two-way layout. The results of our simulation indicate that the latent normal approach is superior to the Wilcoxon–Mann–Whitney test. Clinical examples are used to illustrate our suggested testing methods.     

损失模拟模型的模拟与检验

为帮助精算师在不同的数据环境下选择最优的准备金评估方法,美国非寿险精算师协会组织开发了一个产生模拟索赔数据的开源软件系统——损失模拟模型,然而损失模拟模型是否能够按指定参数要求产生模拟数据需要进行检验.文章采用不同的参数估计方法和拟合优度检验方法对模拟索赔次数的分布、索赔额的趋势以及不同险种索赔次数之间的相关结构进行了统计检验,结果表明损失模拟模型对索赔次数的分布、索赔额的趋势能够产生一致的模拟,而对索赔次数数据之间相关结构的模拟存在不稳定性.     

中国城乡发展差距水平及其波动效应的实证

城乡发展差距是中国社会转型下最突出的矛盾之一.文章从经济、社会、文化、政治、生态五大维度构建中国城乡发展差距综合评价指标体系,以中国31个省份为研究区域,运用主成分分析法实证评价了中国城乡发展差距的现实水平及其波动效应.研究表明,中国城乡差距水平由东向西呈递增趋势,1985年至今城乡差距水平表现为一种波动性扩大的效应,城乡差距水平与城镇化发展水平表现为一种相互影响的逆向关系.     

国家级新区发展总部经济的扶持政策比较

总部经济是国家级新区竞相培育发展的一种新型经济形态,也是衡量新区区域竞争力的重要指标。以国家级新区总部经济扶持政策为研究对象,重点梳理分析了上海浦东、天津滨海、重庆两江等8个国家级新区扶持总部经济发展的具体政策,总结了新区在总部经济发展扶持政策的通行做法和基本规律,并在此基础上提出新区应加强总部经济规划、总部经济中央商务区建设以及加大优惠扶持政策力度等相关对策建议。     

连片特困区城镇化进程与农民增收效应的空间计量分析——以武陵山片区为例

基于2000—2012年武陵山片区69县市(区)的面板数据,考虑空间异质性,运用空间统计的ESDA法和空间计量等方法,考察了片区农民收入与城镇化进程的空间相关性及其冷热点格局,比较产业城镇化和人口城镇化的农民增收效应。结果表明:(1)武陵山片区各县市(区)农民人均纯收入呈现出高度的空间正相关性,形成以丰都、彭水、武隆、黔江为中心的热点区及洪江、中方和鹤城为中心的次热点区;人口城镇化和产业城镇化空间相关性显著,热点区主要集中在张家界片区,有向周边蔓延趋势;铜仁地区处于"三低"分布的冷点区。(2)进一步的空间模型估计显示,人口城镇化是片区农民增收效应的主要动力,产业城镇化对农民收入增长亦有正效应,但带动能力偏弱。(3)农业技术水平、物质资本投资和经济密度的提高有利于农民增收,相反,片区金融发展的现状对农民增收存在抑制作用。根据以上结论提出了相关政策建议。     

Quantile regression for robust estimation and variable selection in partially linear varying-coefficient models

In this paper, we develop a new estimation procedure based on quantile regression for semiparametric partially linear varying-coefficient models. The proposed estimation approach is empirically shown to be much more efficient than the popular least squares estimation method for non-normal error distributions, and almost not lose any efficiency for normal errors. Asymptotic normalities of the proposed estimators for both the parametric and nonparametric parts are established. To achieve sparsity when there exist irrelevant variables in the model, two variable selection procedures based on adaptive penalty are developed to select important parametric covariates as well as significant nonparametric functions. Moreover, both these two variable selection procedures are demonstrated to enjoy the oracle property under some regularity conditions. Some Monte Carlo simulations are conducted to assess the finite sample performance of the proposed estimators, and a real-data example is used to illustrate the application of the proposed methods.     

Mini-max-risk and mini-mean-risk inferences for a partially piecewise regression

We consider a partially piecewise regression in which the main regression coefficients are constant in all subdomains, but the extraessential regression function is variable in different pieces and is difficult to be estimated. Under this situation, two new regression methodologies are proposed under the criteria of mini-max-risk and mini-mean-risk. The resulting models can describe the regression relations in maximum-risk and mean-risk environments, respectively. A two-stage estimation procedure, together with a composite method, is introduced. The asymptotic normality of the estimators is established, the standard convergence rate and efficiency are achieved. Some unusual features of the new estimators and predictions, and the related variable selection are discussed for a comprehensive comparison. Simulation studies and a real-financial example are given to illustrate the new methodologies.     

Precise large deviations for φ-mixing and UND random variables with long-tailed distributions

In this paper, we investigate the precise large deviations for sums of φ-mixing and UND random variables with long-tailed distributions. The asymptotic relations for non random sum and random sum of random variables with long-tailed distributions are obtained.     

Stereotype and National Attachment in Hong Kong Chinese Context: A Moderated Mediation Model of Perceived Inter-group Relationship and Age

The present study investigated the relationship between Hong Kong people’s stereotype toward Mainland people and their own national attachment (i.e., national identity, constructive patriotism, and uncritical patriotism). The role of inter-group relationship as mediator and age as moderator of that relationship were also tested. A total of 1753 local Hong Kong people aged 17–80 (mean age = 20.35 years, SD = 5.02) completed anonymous questionnaires regarding their stereotypes toward Mainland people, inter-group relationship with Mainland people, and national attachment. As expected, stereotypes toward Mainland people, inter-group relationship and national attachment showed significant positive associations with each other. More interestingly, it was found that the inter-group relationship mediated the relationship between stereotypes toward Mainland people and three domains of national attachment, with this indirect link being weaker for younger Hong Kong adults than for older Hong Kong adults. Implications of the present findings for future research are discussed, as well as potential interventions for increasing subjective national attachment to China, especially in young Hong Kong people.     

Characteristics of atmospheric PM2.5 in stands and non-forest cover sites across urban-rural areas in Beijing,China

Urban Ecosystems - Monitoring air pollution at a city scale is essential for controlling urban air pollution in cities, especially megacities, in China. In this paper, data for 1 city center site...