SEMDS: An R Package for Structural Equation Multidimensional Scaling

The aim of this article is to introduce the R package semds for structural equation multidimensional scaling. This methodology combines multidimensional scaling with latent variable features from structural equation modeling and is applicable to asymmetric and three-way input dissimilarity data. This key idea of this approach is that the input data are assumed to be imperfect measurements of a latent symmetric dissimilarity matrix. The parameter estimation is performed via an alternating least squares multidimensional scaling procedure that minimizes the stress. The latent dissimilarities are estimated as factor scores within a structural equation modeling framework. Applications shown in the article involve data associated with the banking crisis and data from avalanche research. The models fitted with the semds package are compared to related methods from multidimensional scaling. The R code to reproduce all the computations is provided in the supplementary materials.     

Using ΔGoodness-of-Fit Indexes in Assessing Mean Structure Invariance

A multidimensional scaling (MDS) model is proposed for 2-way 1-mode asymmetric dissimilarity data, to estimate the unknown symmetric subjacent dissimilarity matrix while the objects are represented in a low-dimensional space. In the context of least squares MDS allowing transformations, and considering both triangular parts of the asymmetric dissimilarity matrix as effects of the unobserved symmetric dissimilarities, an alternating estimation procedure is proposed in which the unknown symmetric dissimilarity matrix is estimated in a covariance structure framework. Real and artificial data are analyzed to illustrate the proposed procedure.     

Effects of confidence and anxiety on flow state in competition

Abstract

Confidence and anxiety are important variables that underlie the experience of flow in sport. Specifically, research has indicated that confidence displays a positive relationship and anxiety a negative relationship with flow. The aim of this study was to assess potential direct and indirect effects of confidence and anxiety dimensions on flow state in tennis competition. A sample of 59 junior tennis players completed measures of Competitive State Anxiety Inventory-2d and Flow State Scale-2. Following predictive analysis, results showed significant positive correlations between confidence (intensity and direction) and anxiety symptoms (only directional perceptions) with flow state. Standard multiple regression analysis indicated confidence as the only significant predictor of flow. The results confirmed a protective function of confidence against debilitating anxiety interpretations, but there were no significant interaction effects between confidence and anxiety on flow state.     

跨文化交际中心理定势的多维视角研究

文章首先介绍了国内外学者对心理定势的定义从负面到中性的转变,接着从社会文化、社会心理和社会认知三个角度对心理定势的产生和发展、特征、分类、解构和建构、模糊范畴等进行了全面的考察,最后讨论了心理定势对英语教学的启示.     

中国和平发展与新军事变革

国防现代化是中国和平发展的必然选择,是我国必须坚持的现代国防理念。从国防理念的演化来说,在历史上大体经历了陆权国防理念、海权国防理念、空权国防理念和多维国防理念等四个阶段。多维国防理念指导下的现代战争具有信息化、非接触性、控制太空以及综合化指挥艺术等特点。为了维护我国主权安全、实现国家统一、保障经济社会的可持续发展、促进世界和平,中国必须大力推进新军事变革。     

基于共词分析的微生物学植物学领域研究热点分析

为了解农业领域中微生物学、植物学领域的研究热点及走向,本文采用共词分析的方法,通过Excel、SPSS等软件,对CNKI数据库中2004-2014年间1604篇相关文献进行统计。通过分析得出高频关键词并建立共词矩阵。进一步对高频词共词矩阵进行聚类分析和多维尺度分析,认为植物、微生物领域研究热点主要集中在基因方面的研究进展、植物的应用分析、微生物的物理分析、生物技术及特性分析等四大主题上。其中在基因方面的研究进展属于最热门的研究领域。     

数据仓库技术与多维数据集实现

随着数据库技术的发展和数据库管理系统的广泛应用,人们积累的数据越来越多,出现了"数据拥挤"现象.数据仓库可以对数据进行有效集成,是数据分析与决策支持的基础,是把数据转换成信息知识的关键技术.     

comparison of three growth modeling techniques in the multilevel analysis of longitudinal academic achievement scores: Latent growth modeling, hierarchical linear modeling, and longitudinal profile analysis via multidimensional scaling

This study introduces three growth modeling techniques: latent growth modeling (LGM), hierarchical linear modeling (HLM), and longitudinal profile analysis via multidimensional scaling (LPAMS). It compares the multilevel growth parameter estimates and potential predictor effects obtained using LGM, HLM, and LPAMS. The purpose of this multilevel growth analysis is to alert applied researchers to selected analytical issues that are required for consideration in decisions to apply one of these three approaches to longitudinal academic achievement studies. The results indicated that there were no significant distinctions on either mean growth parameter estimates or on the effects of potential predictors to growth factors at both the student and school levels. However, the study also produced equivocal findings on the statistical testing of variance and covariance growth parameter estimates. Other practical issues pertaining to the three growth modeling methods are also discussed.     

多维度视域下半工半读办学模式探索

《国家职业教育改革实施方案》的发布使企业和学校再一次紧密地联系起来。文章从国家、学校、企业、学生、家庭等五个维度对半工半读办学模式发展现状和存在的困境进行探讨,提出加强顶层设计、学校管理,激发学生内动力,增强企业参与的积极性,加强家校合作等对策建议。     

物理教学中思维能力的培养

物理教学中必须重视学生思维能力的培养,具体方法有:一、精心创设疑点,巧妙启发思维;二、打破“思维定势”,培养发散思维;三、拓宽思维空间,培养逆向思维。