An assessment of the use of the continuity correction for sparse data in meta-analysis

A problem which occurs in the practice of meta-analysis is that one or more component studies may have sparse data, such as zero events in the treatment and control groups. Two possible approaches were explored using simulations. The corrected method, in which one half was added to each cell was compared to the uncorrected method. These methods were compared over a range of sparse data situations in terms of coverage rates using three summary statistics:the Mantel-Haenszel odds ratio and the dersimonian and Laird odds ratio and rate difference. The uncorrected method performed better only when using the Mantel-Haenszel odds ratio with very little heterogeneity present. For all other sparse data applications, the continuity correction performed better and is recommended for use in meta-analyses of similar scope     

Bootstrap confidence regions for correspondence analysis

A bootstrap-based method for constructing confidence regions (CRs) around row or column points projected onto a pair of axes from the correspondence analysis (CA) of a two-way contingency table is presented. These regions deal with the specific question of the sampling variation of sample row and column profile points around population row and column profile points when both are projected onto the observed axes, rather than the decomposition of the χ²-test of independence or the general question of the stability of the observed CA display which has been considered in previous work. The method therefore constructs the regions in a different way to what has been proposed before. A simulation experiment shows that the method performs well in most of the situations in which it might be used, with a few exceptions being noted. An example illustrates that the method produces conclusions which are consistent with those from detailed parametric modelling.     

判别分析统计检验体系的探讨

判别分析已越来越受到人们的重视并取得了重要的应用成果,但应用中存在着简单套用的情况,对判别分析的适用性、判别效果的显著性、判别变量的判别能力以及判别函数的判别能力的检验等问题重视不够。为了更好地应用判别分析,就应对判别分析进行统计检验并建立统计检验体系,统计检验体系应包括：判别分析适用性检验,判别效果显著性检验,判别变量的判别能力检验和判别函数的判别能力检验。     

论中国区域协调发展战略的必要性

中国区域经济结构面临着两大问题,即区域产业结构的趋同性和区域之间发展差距的不断扩大,这严重地制约了中国整体经济的进一步发展.中国区域协调发展战略的提出是中国区域经济发展的客观要求,也是形成全国统一市场和启动内需市场的必然选择.     

创新：破解高校学报同质化难题

高校学报是我国期刊方阵的重要力量。但国内高校学报同质化的现象十分突出,如何解决高校学报同质化问题的方法和路径很多,其中创新是十分重要的解决办法。没有创新的高校学报是没有竞争力,没有竞争力就没有高校学报生命力。高校学报要高举学术创新的旗帜,全力打造高校学报的品牌,办成创新学报和精品学报,才能在知识经济中占有一席之地。     

论法律人的养成

法律人 (lawyer)是对具有同质性的法律职业者的概称 ,其同质性体现在知识结构、思维方式、价值理念等方面。法律人是法治社会必然出现也无法回避的精英现象。欲实现法治 ,所有的法律人必须形成一个强有力的共同体 ,担当先锋重任。其培养不是简单的工匠式的训练 ,而应该是一套完备的制度体系 ,即法律教育、司法训练和职业纪律规范三位一体、协调统一。我国法律人养成的路径 :应理出一条清晰的思路 ,使法律人的培养制度化。     

Algorithms for the construction of optimizing distributions

We will consider the following problem.Maximise Φ(p)over P={p=(p₁,P₂,…,p_j):P_j≧0,∑p_j=1}". We require to calcute an optimizing distribution. Examples arise in optimal regression design,maximum likelihood estimation and stratified sazmpling problems. A class of multiplicative algorithms, indexed by functions which depend on the derivatives of Φ(·)is considered for solving this problem.Iterations are of the form:p_j ^(r+1)αp_j ^(r)f(x_j ^(r)), where x_{j (r)}=d_j ^(r) or F_j ^(r)and d_j ^(r)=?Φ/?p_j While F_j ^(r)=D_j ^(r)?∑p_i ^(r)d_i ^(r) (a directional derivative)at p=p^(r)f(·)satisfies some suitable properties and may depend on one or more free parameters. These iterations neatly submit to the constraints ofv the problem. Some results will be reported and extensions to problems dependin on two or more distributions and to problems with additional constraints will be considered.     

Nonparametric Estimation of Nonadditive Random Functions

We present estimators for nonparametric functions that are nonadditive in unobservable random terms. The distributions of the unobservable random terms are assumed to be unknown. We show that when a nonadditive, nonparametric function is strictly monotone in an unobservable random term, and it satisfies some other properties that may be implied by economic theory, such as homogeneity of degree one or separability, the function and the distribution of the unobservable random term are identified. We also present convenient normalizations, to use when the properties of the function, other than strict monotonicity in the unobservable random term, are unknown. The estimators for the nonparametric function and for the distribution of the unobservable random term are shown to be consistent and asymptotically normal. We extend the results to functions that depend on a multivariate random term. The results of a limited simulation study are presented.