A method for analyzing changes in response efficiency.

Although experimental effects typically are evaluated by summarizing levels of responding across time (e.g., calculating the mean levels of problem behavior during 10‐min sessions), these data summaries may obscure important mechanisms that may be responsible for changes in responding. A case study is reported to illustrate alternative methods of data analysis when decreasing trends in responding may be due to increases in response efficiency.     

A variable-selection heuristic for K-means clustering

One of the most vexing problems in cluster analysis is the selection and/or weighting of variables in order to include those that truly define cluster structure, while eliminating those that might mask such structure. This paper presents a variable-selection heuristic for nonhierarchical (K-means) cluster analysis based on the adjusted Rand index for measuring cluster recovery. The heuristic was subjected to Monte Carlo testing across more than 2200 datasets with known cluster structure. The results indicate the heuristic is extremely effective at eliminating masking variables. A cluster analysis of real-world financial services data revealed that using the variable-selection heuristic prior to the K-means algorithm resulted in greater cluster stability.     

God as Spirit—and Natural Science

The biblical sentence "God is Spirit" (John 4:24) occasioned the development of the Christian doctrine about God as Spirit. But since patristic times "spirit" was interpreted in the sense of Nus, which rather means "intellect." The biblical concept of spirit (pneuma), however, has its root meaning in referring to "air in movement," as in breath or storm. The similar concept of pneuma in Stoic philosophy has become the "immediate precursor" (Max Jammer) of the field concept in modern physics, so that the conclusion is suggested that God is spirit as something like a field of force rather than as intellect. This essay argues for such a conception by relating the divine eternity and immensity to the concepts of space and time, the basic requirements of any physical field. God's eternity and immensity are interpreted in terms of undivided infinite space (and time) which is presupposed in all concepts of parts of space or time (or space-time), therefore in all mathematical and physical measurement.     

多项式回归与一致性研究：应用及分析

本文介绍了多项式回归的分析方法, 讨论并验证了它相比传统的差异分数分析法在检验一致性假设中的优势。针对目前该方法在国内应用方面的缺失状况, 本文从分析基准、理论推导、分析步骤和假设检验等方面完善了多项式回归与响应面分析相结合的应用分析框架。最后, 本文以个人-组织价值观一致性对员工情感性变革承诺的影响研究为例, 对分析框架的具体应用进行了说明。结果表明, 被传统差异分数很好支持的一致性效应并不一定完美, 新的分析框架能够揭示更多的有用信息并给管理实践带来更具体而准确的引导。     

Social networks with two sets of actors

Traditional network research analyzes relational ties within a single group of actors: the models presented in this paper involve relational ties exist beteen two distinct sets of actors. Statistical models for traditional networks in which relations are measured within a group simplify when modeling unidirectional relations measured between groups. The traditional paradigm results in a one-mode socionatrix; the network paradigm considered in this paper results in a two-mode socionatrix; A statistical model is presented, illustrated on a sample data set, and compared to its traditional counterpart. Extensions are discussed, including those that model multivariate relations simultaneously, and those that allow for the inclustion of attributes of the individuals in the group.We thank the Editor and two anonymous reviewers for their helpful comments. We are also grateful to George Barnett for allowing us to analyze his data.     

大学生学习适应量表的编制

对当代大学生学习适应问题进行了深入分析,在有关研究的基础上,探讨了当代大学生学习适应的主要因素,并编制一套适合当代大学生学习适应的测验。对四类院校918名大学生进行了施测,对调查数据进行了探索性因素分析和验证性因素分析。探索性因素分析结果表明,大学生学习适应的主要因素包括学习动机、教学模式、学习能力、学习态度、环境因素等5个方面;验证性因素分析结果表明,所提取的5个因素与构想模型拟合较好,测验具有较好的信、效度     

儿童学校适应的分类及判定

以6579名小学三、五年级学生为被试,采用聚类分析和判别分析方法,结果表明:(1)根据儿童学校适应的指标将儿童的学校适应状况分为良好型、闲适型、紧张型、高危型四种类型.(2)良好型的儿童,在学业自我评估、学业动机和心理健康水平三个水平上的得分为正向,在问题行为上的得分为负;高危型儿童的结果与适应良好型的儿童完全相反;而在闲适型的儿童中,学业动机为负、心理健康水平为正;在紧张型的儿童中,学业动机为正向、而心理健康水平是负向的.(3)建立儿童学校适应的判别函数,为儿童在教育和心理问题进行指导提供了初步诊断依据,同时也对有关学校适应的研究提供新的视角.     

条件反射性抗体反应增强的动态分析——以OVA为非条件刺激物

研究了条件反射性抗体反应增强模型的建立。被试为49只雄性成年Wistar大鼠,采用糖精水作为条件性刺激,一种蛋白抗原卵清蛋白作为非条件性刺激配对给予大鼠,两者结合后,在初次抗体应答下降阶段再次单独给予条件刺激,用酶联免疫吸附法分时段检测抗体水平的变化。发现条件组在条件刺激后15,20,25天左右抗体水平明显高于对照组。这一过程与初次抗体应答的规律类似。这些结果证实经一次条件训练,单独给予条件刺激能诱导出明显的条件反射性抗体反应增高。     

情绪智力的基础：情绪觉察的研究现状与展望

情绪觉察作为情绪智力的重要基础,指的是识别与描述自己和他人情绪的能力,对个体的心理健康,人际交往具有重要意义。为系统考察情绪觉察的研究现状,采用定性和定量相结合的方式回顾以往研究,即先采用文献计量学的方法定量分析该领域研究的概况,然后在此基础上,对研究的具体内容从概念界定、测量工具、神经基础、相关因素和干预研究五个方面作进一步系统梳理。最后,对以往研究进行了总结和展望,以期为今后研究提供借鉴。     

A cautionary note on using internal cross validation to select the number of clusters

A highly popular method for examining the stability of a data clustering is to split the data into two parts, cluster the observations in Part A, assign the objects in Part B to their nearest centroid in Part A, and then independently cluster the Part B objects. One then examines how close the two partitions are (say, by the Rand measure). Another proposal is to split the data into k parts, and see how their centroids cluster. By means of synthetic data analyses, we demonstrate that these approaches fail to identify the appropriate number of clusters, particularly as sample size becomes large and the variables exhibit higher correlations.The authors express their thanks to the Sol C. Snider Entrepreneurial Center, Wharton School, for support of this project.