谈多媒体环境下的英语教学策略

依据教育学、心理学有关理论,从教学环节入手,探讨了英语教学在多媒体环境下的教学策略选择原则及相应英语教学策略,提出英语教学的整体筹划策略、信息输入策略、全息评价策略和重现巩固策略。     

关于元评估

本文阐述了元评估工作的重要意义 ,并对元评估活动所依据的原则 (客观性、整体性　全面性、综合性 )、应遵循的程序和采用的方法 (元研究方法、系统方法、评价方法、模型方法 )作了系统论述。元评估活动将对提高各级领导决策的科学性和自觉性 ,推动社会各个领域乃至整个社会与自然界协调而持续的发展作出宝贵的贡献     

英美法系和大陆法系刑事陪审制度功能之比较

陪审制度的功能是陪审制度得以存在和延续的理由 ,笔者首先剖析了陪审制度的沿革及其发展趋势 ;进而阐述陪审制度在两大法系中共有的功能 ;最后分别阐述英美法系和大陆法系刑事陪审制度功能     

刑事诉讼主体的法理分析--以刑事法律关系为基础

犯罪行为引起的刑事法律关系是考察刑事诉讼主体问题的真正法理基础。国家与被告人作为刑事法律关系的主体是刑事诉讼的当事人 ,被害人及其近亲属不是刑事法律关系的主体 ,故不是刑事诉讼当事人 ,只是发动、支持公法性诉讼的公民追诉人。审判权与公诉权的分立 ,本质上是国家将自身作为自己的对象 ,并在自己(裁判者 )与作为对象的自身 (当事人 )之间建立绝对区分 ,体现了作为公共权力的国家的自我反思节制。其他刑事诉讼主体均不是刑事法律关系的主体 ,按照意志关系或者是国家的代表、被告人和被害人的代理人或帮助人 ,或者是不从属于任何一方的诉讼主体。     

证据不足的无罪判决之评析

证据不足的无罪判决是疑罪从无原则在审判活动中的体现,其性质归属实际上就是无罪判决,为了调和人民法院裁判的稳定性、权威性和裁判的公正性之间的关系,此类判决在撤销或变更上应适用因新发现的情况而恢复诉讼的程序。     

Empirical likelihood confidence intervals for the mean of a population containing many zero values

If a population contains many zero values and the sample size is not very large, the traditional normal approximation‐based confidence intervals for the population mean may have poor coverage probabilities. This problem is substantially reduced by constructing parametric likelihood ratio intervals when an appropriate mixture model can be found. In the context of survey sampling, however, there is a general preference for making minimal assumptions about the population under study. The authors have therefore investigated the coverage properties of nonparametric empirical likelihood confidence intervals for the population mean. They show that under a variety of hypothetical populations, these intervals often outperformed parametric likelihood intervals by having more balanced coverage rates and larger lower bounds. The authors illustrate their methodology using data from the Canadian Labour Force Survey for the year 2000.     

论我国民事诉讼证据保全制度及其完善

证据保全是法院对证据采取保护措施、保证其证明力的一种制度,包括诉前证据保全与诉讼中的证据保全。我国民事诉讼证据保全制度并不完善,应当规定全面的证据保全制度,即对诉前证据保全制度应当加以规定;另外,还要完善证据保全的具体程序与规定证据保全申请错误的赔偿和诉讼等。     

Non-ignorable missing covariate data in survival analysis: a case-study of an International Breast Cancer Study Group trial

Summary.  Non-ignorable missing data, a serious problem in both clinical trials and observational studies, can lead to biased inferences. Quality-of-life measures have become increasingly popular in clinical trials. However, these measures are often incompletely observed, and investigators may suspect that missing quality-of-life data are likely to be non-ignorable. Although several recent references have addressed missing covariates in survival analysis, they all required the assumption that missingness is at random or that all covariates are discrete. We present a method for estimating the parameters in the Cox proportional hazards model when missing covariates may be non-ignorable and continuous or discrete. Our method is useful in reducing the bias and improving efficiency in the presence of missing data. The methodology clearly specifies assumptions about the missing data mechanism and, through sensitivity analysis, helps investigators to understand the potential effect of missing data on study results.     

Merging information for semiparametric density estimation

Summary.  The density ratio model specifies that the likelihood ratio of m −1 probability density functions with respect to the m th is of known parametric form without reference to any parametric model. We study the semiparametric inference problem that is related to the density ratio model by appealing to the methodology of empirical likelihood. The combined data from all the samples leads to more efficient kernel density estimators for the unknown distributions. We adopt variants of well-established techniques to choose the smoothing parameter for the density estimators proposed.     

Assessing goodness-of-fit of categorical regression models based on case-control data

Demonstrated equivalence between a categorical regression model based on case‐control data and an I‐sample semiparametric selection bias model leads to a new goodness‐of‐fit test. The proposed test statistic is an extension of an existing Kolmogorov–Smirnov‐type statistic and is the weighted average of the absolute differences between two estimated distribution functions in each response category. The paper establishes an optimal property for the maximum semiparametric likelihood estimator of the parameters in the I‐sample semiparametric selection bias model. It also presents a bootstrap procedure, some simulation results and an analysis of two real datasets.