Mean estimation through proportion estimation

In this work a device which changes the problem of mean estimation into that of proportion estimation is proposed. The device consists of perturbing the observations. The goal of the work is the construction of conservative confidence intervals for means. Three applications are given: (1) proportion estimation in the context of cluster random sampling, (2) differences of proportions of a multinomial population and (3) variance estimation.     

Conditionally exponential random models for individual properties and network structures: Method and application

Exponential random models have been widely adopted as a general probabilistic framework for complex networks and recently extended to embrace broader statistical settings such as dynamic networks, valued networks or two-mode networks. Our aim is to provide a further step into the generalization of this class of models by considering sample spaces which involve both families of networks and nodal properties verifying combinatorial constraints. We propose a class of probabilistic models for the joint distribution of nodal properties (demographic and behavioral characteristics) and network structures (friendship and professional partnership). It results in a general and flexible modeling framework to account for homophily in social structures. We present a Bayesian estimation method based on the full characterization of their sample spaces by systems of linear constraints. This provides an exact simulation scheme to sample from the likelihood, based on linear programming techniques. After a detailed analysis of the proposed statistical methodology, we illustrate our approach with an empirical analysis of co-authorship of journal articles in the field of neuroscience between 2009 and 2013.     

Simulation and Analytical Approach to the Identification of Significant Factors

We develop our previous works concerning the identification of the collection of significant factors determining some, in general, nonbinary random response variable. Such identification is important, e.g., in biological and medical studies. Our approach is to examine the quality of response variable prediction by functions in (certain part of) the factors. The prediction error estimation requires some cross-validation procedure, certain prediction algorithm, and estimation of the penalty function. Using simulated data, we demonstrate the efficiency of our method. We prove a new central limit theorem for introduced regularized estimates under some natural conditions for arrays of exchangeable random variables.     

Asymptotic normality of kernel estimators based upon incomplete data

In this paper, we are concerned with nonparametric estimation of the density and the failure rate functions of a random variable X which is at risk of being censored. First, we establish the asymptotic normality of a kernel density estimator in a general censoring setup. Then, we apply our result in order to derive the asymptotic normality of both the density and the failure rate estimators in the cases of right, twice and doubly censored data. Finally, the performance and the asymptotic Gaussian behaviour of the studied estimators, based on either doubly or twice censored data, are illustrated through a simulation study.     

Different methods for handling incomplete longitudinal binary outcome due to missing at random dropout

This paper compares the performance of weighted generalized estimating equations (WGEEs), multiple imputation based on generalized estimating equations (MI-GEEs) and generalized linear mixed models (GLMMs) for analyzing incomplete longitudinal binary data when the underlying study is subject to dropout. The paper aims to explore the performance of the above methods in terms of handling dropouts that are missing at random (MAR). The methods are compared on simulated data. The longitudinal binary data are generated from a logistic regression model, under different sample sizes. The incomplete data are created for three different dropout rates. The methods are evaluated in terms of bias, precision and mean square error in case where data are subject to MAR dropout. In conclusion, across the simulations performed, the MI-GEE method performed better in both small and large sample sizes. Evidently, this should not be seen as formal and definitive proof, but adds to the body of knowledge about the methods’ relative performance. In addition, the methods are compared using data from a randomized clinical trial.     

语言经济原则下的交际语用失误成因分析

在语言的使用过程中，不仅语言本身会影响语言交际，语用因素也在其中起到了至关重要的作用，所以，在交际中，特别是跨文化交际中，语用失误会直接影响语言交际的有效性。本文将从语言的最基本属性之一——经济原则为基本出发点，对交际语用失误进行分析，指出交际语用失误是由交际参与者对缺省信息填补过程中在认知语境、文化规约以及思维方式方面信息获取的错失或不当所引起的。     

Parenting in Relation to School Dropout Through Student Engagement: A Longitudinal Study

Dropping out of school generally has negative consequences for both individuals and society, and the decision to do so has been described as a crucial developmental task of adolescence. This longitudinal study examined the contribution of parenting practices to students' completion of upper secondary school through their school engagement. Icelandic youth (N = 835, 54% female) were followed from age 14 to 22. Analyses using structural equation modeling revealed that adolescents (age 14) with more authoritative parents (high acceptance, supervision, and psychological autonomy granting) were more likely to have graduated at age 22 compared to adolescents with less authoritative parents. Moreover, the level of student engagement at age 15 partly mediated the relationship between authoritative parenting and educational status. These findings emphasize the importance of quality parent–child relationships to enhance adolescents' school engagement, which in turn reduces the risk of school dropout.     

耦合分析混凝土结构缺陷的发展综述

应用断裂力学与损伤力学耦合分析方法分析混凝土破坏的问题是目前混凝土结构损伤研究的新趋势.以三点弯曲混凝土梁为例，阐明如何运用断裂损伤力学耦合分析方法初步确定结构缺陷区域，然后用断裂损伤理论及有限元方法模拟结构破坏过程.通过三点弯曲混凝土梁损伤分析以及对不同损伤本构模型方程的建立及分歧讨论，揭示混凝土损伤本构的发展方向和前景.可视化程序的引入对混凝土损伤本构关系的研究既是挑战也是机遇，损伤本构模型的建立最终目的是要服务于实际生产.     

强扰动理论及其发展

从矩阵形式的麦克斯韦方程出发,对强扰动理论有了重要的发展,使它不仅能处理强扰动随机电介质的问题,而且可以处理强扰动电、磁混合媒质电磁散射的计算。作为应用新理论的例子,文中详细地讨论了颗粒媒质等效介电常数和等效导磁率的计算。结果表明,当粒子线度比波长小得多时,媒质粒子的介电常数和导磁率之间互不影响。     

Market overreach: The student as customer

This paper explores the market model's influence in redefining the relationship between teachers and students within the college and university. Viewing the student as a customer rather than as a “worker” or “apprentice” is argued to have created several problems. The case is made that with market forces leading to the substitution of purchased commodities for “production for self,” the role of the student in actively participating in the learning process is threatened. Several trends, including grade inflation, shortened contact hours, and the redefinition of study time are offered as evidence that the non-salable components of higher education are declining in importance.