贫困测量中恩格尔系数的失效及分析

 恩格尔系数在我国的适用性问题是学术界重要议题之一。本文利用对哈尔滨市和沈阳市贫困人口的调查数据,分析了恩格尔系数在我国城市贫困测量中失效的问题及原因。研究者尝试对恩格尔系数的分子、分母进行了重新界定和适当的修正,研究检验表明,从宏观测量和微观测量两个方面,修正恩格尔系数都能更准确的反映我国城市贫困家庭的真实生活水平。     

变数额标准为人员标准——农村低保标准确定的范式转换

中国扶贫和发展的情况表明,要解决农村全部贫困人员的温饱问题必须建立农村低保制度。受扶贫和城市低保对像确认的影响,我国实行农村低保试点的地区多采取数额标准作为确定农村低保对象的主要确认方法。鉴于数额标准在确定农村低保对象中的种种缺陷和弊端,文章在分析农村低保意义的基础上论证了变数额标准为人员标准在农村低保对象确认中的意义、作用、应注意的问题和确认的方法。     

应用同伦正则化算法反演二维溶质运移模型中的弥散系数

利用同伦正则化算法探讨了二维对流弥散方程的依赖空间变量的弥散系数反演问题.讨论了初始迭代值、数值微分步长、以及收敛精度对算法实现的影响.数值模拟表明,同伦正则化算法对于此类参数反演问题是一种有效的方法.     

Approximate confidence intervals for the weighted kappa coefficient of a binary diagnostic test subject to a case–control design

Case–control design to assess the accuracy of a binary diagnostic test (BDT) is very frequent in clinical practice. This design consists of applying the diagnostic test to all of the individuals in a sample of those who have the disease and in another sample of those who do not have the disease. The sensitivity of the diagnostic test is estimated from the case sample and the specificity is estimated from the control sample. Another parameter which is used to assess the performance of a BDT is the weighted kappa coefficient. The weighted kappa coefficient depends on the sensitivity and specificity of the diagnostic test, on the disease prevalence and on the weighting index. In this article, confidence intervals are studied for the weighted kappa coefficient subject to a case–control design and a method is proposed to calculate the sample sizes to estimate this parameter. The results obtained were applied to a real example.     

Continuity of f-projections and applications to the iterative proportional fitting procedure*

This paper proves continuity of f-projections and the continuous dependence of the limit matrix of the iterative proportional fitting procedure (IPF procedure) on the given matrix as well as the given marginals under certain regularity constraints. For finite spaces, the concept of f-projections of finite measures on a compact and convex set is introduced and continuity of f-projections is proven. This result is applied to the IPF procedure. Given a nonnegative matrix as well as row and column marginals the IPF procedure generates a sequence of matrices, called the IPF sequence, by alternately fitting rows and columns to match their respective marginals. The procedure is equivalent to cyclic f-projections. If the IPF sequence converges, the application of the continuity of f-projections yields the continuous dependence of the limit matrix on the given matrix. By generalized convex programming and under some constraints, it is shown that the limit matrix of the IPF sequence continuously depends not only on the given matrix but also on the marginals.     

Unified Inference for Sparse and Dense Longitudinal Data in Time‐varying Coefficient Models

Time‐varying coefficient models are widely used in longitudinal data analysis. These models allow the effects of predictors on response to vary over time. In this article, we consider a mixed‐effects time‐varying coefficient model to account for the within subject correlation for longitudinal data. We show that when kernel smoothing is used to estimate the smooth functions in time‐varying coefficient models for sparse or dense longitudinal data, the asymptotic results of these two situations are essentially different. Therefore, a subjective choice between the sparse and dense cases might lead to erroneous conclusions for statistical inference. In order to solve this problem, we establish a unified self‐normalized central limit theorem, based on which a unified inference is proposed without deciding whether the data are sparse or dense. The effectiveness of the proposed unified inference is demonstrated through a simulation study and an analysis of Baltimore MACS data.     

Estimation and Inference Procedures for Semiparametric Distribution Models with Varying Linear‐Index

More flexible semiparametric linear‐index regression models are proposed to describe the conditional distribution. Such a model formulation captures varying effects of covariates over the support of a response variable in distribution, offers an alternative perspective on dimension reduction and covers a lot of widely used parametric and semiparameteric regression models. A feasible pseudo likelihood approach, accompanied with a simple and easily implemented algorithm, is further developed for the mixed case with both varying and invariant coefficients. By justifying some theoretical properties on Banach spaces, the uniform consistency and asymptotic Gaussian process of the proposed estimator are also established in this article. In addition, under the monotonicity of distribution in linear‐index, we develop an alternative approach based on maximizing a varying accuracy measure. By virtue of the asymptotic recursion relation for the estimators, some of the achievements in this direction include showing the convergence of the iterative computation procedure and establishing the large sample properties of the resulting estimator. It is noticeable that our theoretical framework is very helpful in constructing confidence bands for the parameters of interest and tests for the hypotheses of various qualitative structures in distribution. Generally, the developed estimation and inference procedures perform quite satisfactorily in the conducted simulations and are demonstrated to be useful in reanalysing data from the Boston house price study and the World Values Survey.     

Computational approach test for inference about several correlation coefficients: Equality and common

In this article, we consider inference about the correlation coefficients of several bivariate normal distributions. We first propose computational approach tests for testing the equality of the correlation coefficients. In fact, these approaches are parametric bootstrap tests, and simulation studies show that they perform very satisfactory, and the actual sizes of these tests are better than other existing approaches. We also present a computational approach test and a parametric bootstrap confidence interval for inference about the parameter of common correlation coefficient. At the end, all the approaches are illustrated using two real examples.     

基于网络环境的研究生英语教学模式研究

传统的非英语专业研究生英语教学模式已不能适应为社会培养创新复合型人才的需要,对其进行改革势在必行。文章以建构主义学习理论和语言输入与输出理论为基础,构建了一种利用互联网资源辅助研究生英语课堂的教学模式,目的旨在提高非英语专业硕士研究生的英语交际能力。     

输入模态对认知负荷及听力成绩的影响

探讨了输入模态对学生认知负荷和听力理解的影响。90名来自两个平行班的大学英语学生被平均分为三个小组参加实验:文本输入组,声音输入组,文本和声音输入组。文本组的听力题目用文本呈现,声音组的听力题目仅用声音呈现,文本和声音组的题目则是采用文本和声音双重模态呈现。认知负荷量表结果和听力测试结果显示不同模态的听力输入形式对听力成绩有显著影响:文本组学生的成绩最高,其次是文本加音频组,音频输入组的成绩最低。认知负荷量表结果显示文本组的认知负荷最低,然后是文本加音频组,音频输入组的认知负荷最高。认知负荷与听力成绩的相关分析显示负荷程度与听力成绩呈负相关。研究结果对听力教学有较好的借鉴作用。