2005年汇改后人民币汇率多次结构突变检验分析——基于循序检验方法

采用最新的多次结构突变循序检验方法,对2005年7月21日汇改后人民币汇率时间序列趋势项是否具有多次结构突变进行研究,并在多次结构突变检验结果的基础上对消除趋势后的人民币汇率数据进行分析,结果发现：人民币汇率时间序列是围绕着4个结构断点的分段趋势平稳的;人民币汇率服从分段趋势平稳的结论对汇率政策有效性、汇率与其他经济总量关系研究及汇率预测具有重要意义。     

GMM in linear regression for longitudinal data with multiple covariates measured with error

Griliches and Hausman 5 Griliches, Z. and Hausman, J. A. 1986. Errors in variables in panel data. J. Econometrics, 32: 93–118. [Crossref], [Web of Science ®] [Google Scholar] and Wansbeek 11 Wansbeek, T. J. 2001. GMM estimation in panel data models with measurement error. J. Econometrics, 104: 259–268. [Crossref], [Web of Science ®] [Google Scholar] proposed using the generalized method of moments (GMM) to obtain consistent estimators in linear regression models for longitudinal data with measurement error in one covariate, without requiring additional validation or replicate data. For usefulness of this methodology, we must extend it to the more realistic situation where more than one covariate are measured with error. Such an extension is not straightforward, since measurement errors across different covariates may be correlated. By a careful construction of the measurement error correlation structure, we are able to extend Wansbeek's GMM and show that the extended Griliches and Hausman's GMM is equivalent to the extended Wansbeek's GMM. For illustration, we apply the extended GMM to data from two medical studies, and compare it with the naive method and the method assuming only one covariate having measurement error.     

Joint impact of multiple observations on a subset of variables in multiple linear regression

In multiple linear regression analysis, each observation affects the fitted regression equation differently and has varying influences on the regression coefficients of the different variables. Chatterjee & Hadi (1988) have proposed some measures such as DSSE_ij (Impact on Residual Sum of Squares of simultaneously omitting the ith observation and the jth variable), F_j (Partial F-test for the jth variable) and F_j(i) (Partial F-test for the jth variable omitting the ith observation) to show the joint impact and the interrelationship that exists among a variable and an observation. In this paper we have proposed more extended form of those measures DSSE_IJ, F_J and F_J(I) to deal with the interrelationships that exist among the multiple observations and a subset of variables by monitoring the effects of the simultaneous omission of multiple variables and multiple observations.     

A modified false discovery rate multiple-comparisons procedure for discrete data, applied to human immunodeficiency virus genetics

Summary.  To help to design vaccines for acquired immune deficiency syndrome that protect broadly against many genetic variants of the human immunodeficiency virus, the mutation rates at 118 positions in HIV amino-acid sequences of subtype C versus those of subtype B were compared. The false discovery rate (FDR) multiple-comparisons procedure can be used to determine statistical significance. When the test statistics have discrete distributions, the FDR procedure can be made more powerful by a simple modification. The paper develops a modified FDR procedure for discrete data and applies it to the human immunodeficiency virus data. The new procedure detects 15 positions with significantly different mutation rates compared with 11 that are detected by the original FDR method. Simulations delineate conditions under which the modified FDR procedure confers large gains in power over the original technique. In general FDR adjustment methods can be improved for discrete data by incorporating the modification proposed.     

Asymptotic bias in the linear mixed effects model under non-ignorable missing data mechanisms

Summary.  In longitudinal studies, missingness of data is often an unavoidable problem. Estimators from the linear mixed effects model assume that missing data are missing at random. However, estimators are biased when this assumption is not met. In the paper, theoretical results for the asymptotic bias are established under non-ignorable drop-out, drop-in and other missing data patterns. The asymptotic bias is large when the drop-out subjects have only one or no observation, especially for slope-related parameters of the linear mixed effects model. In the drop-in case, intercept-related parameter estimators show substantial asymptotic bias when subjects enter late in the study. Eight other missing data patterns are considered and these produce asymptotic biases of a variety of magnitudes.     

Multiple imputation of missing data with ante-dependence covariance structure

A controlled clinical trial was conducted to investigate the efficacy effect of a chemical compound in the treatment of Premenstrual Dysphoric Disorder (PMDD). The data from the trial showed a non-monotone pattern of missing data and an ante-dependence covariance structure. A new analytical method for imputing the missing data with the ante-dependence covariance is proposed. The PMDD data are analysed by the non-imputation method and two imputation methods: the proposed method and the MCMC method.     

信息技术课程多元智力教学模式探究

多元智力理论超越了传统以语言——数理逻辑能力为中心的智力观念,它的发展对传统学科教育产生了深刻的影响,本文就信息技术课程学科特点,从多元智力角度对教学方法改革进行探讨和研究。     

论高职高专诊所式法律教育教学模式的构建

诊所式法律教育是20世纪60年代兴起的一种比较新型的法学教学模式。在高职高专法学专业引进诊所式法律教育,建立适合高职高专学生的教学模式是十分必要的。在高职高专构建诊所式法律教学模式,应有自己独特的教学对象、教学形式和课程体系。案例教学法、讨论式教学法、角色模拟教学法、单独指导教学法等理应成为高职高专诊所式法律教学的主要方法。     

加强临床实验室建设 促进和谐医院的构建

构建和谐医院既是建设社会主义和谐社会的本质要求,也是新时期医院生存和发展的重要条件。构建和谐医院就是要构建和谐的医患关系、和谐的医疗手段和和谐的医院文化。以人为本、人性化管理和实施医院管理年活动是加强医院管理,建设和谐医院的两个主要手段。临床实验室在和谐医院构建中发挥重要作用,这主要通过全面的实验室质量管理和优质的人性化服务来实现。     

非隶属附属医院内涵建设刍议

结合非隶属附属医院的建设实践,从教育观念、教学意识、师资培训、教学管理和教学条件的改善等方面阐述了做好非隶属附属医院内涵建设的重要性和意义。