Recovery of structure in incomplete data by alscal

A Monte Carlo study was carried out in order to investigate the ability of ALSCAL to recover true structure inherent in simulated proximity measures when portions of the data are missing. All sets of simulated proximity measures were based on 30 stimuli and three dimensions, and selection of missing elements was done randomly. Properties of the simulated data varied according to (a) the number of individuals, (b) the level of random error, (c) the proportion of missing data, and (d) whether the same entries or different entries were deleted for each individual. Results showed that very accurate recovery of true distances, stimulus coordinates, and weight vectors could be achieved with as much as 60% missing data as long as sample size was sufficiently large and the level of random error was low.     

Some results on proper eigenvalues and eigenvectors with applications to scaling

Conditions are given under which the stationary points and values of a ratio of quadratic forms in two singular matrices can be obtained by a series of simple matrix operations. It is shown that two classes of optimal weighting problems, based respectively on the grouping of variables and on the grouping of observations, satisfy these conditions. The classical treatment of optimal scaling of forced-choice multicategory data is extended for these cases. It is shown that previously suggested methods based on reparameterization will work only under very special conditions.     

Constrained multidimensional scaling inN spaces

A gradient method is used to obtain least squares estimates of parameters of them-dimensional euclidean model simultaneously inN spaces, given the observation of all pairwise distances ofn stimuli for each space. The procedure can estimate an additive constant as well as stimulus projections and the metric of the reference axes of the configuration in each space. Each parameter in the model can be fixed to equal some a priori value, constrained to be equal to any other parameter, or free to take on any value in the parameter space. Two applications of the procedure are described.     

Empirically Supported Complexity

Abstract— Over the last 10 years, evidence-based practice in psychology has become synonymous with a particular operationalization of it aimed at developing a list of empirically supported therapies. Although much has been learned since the emergence of the empirically supported therapies movement, its restrictive definition of evidence (excluding, for example, basic science as a source of evidence to be used by clinicians) is problematic, and the assumptions inherent in its nearly exclusive focus on brief, focal treatments for specific disorders are themselves not generally supported by the available data. Recent meta-analytic data support a more nuanced view of treatment efficacy than one that makes dichotomous judgments of empirically supported or unsupported, suggesting the need for a more refined concept of evidence-based practice in psychology.     

A Latent Class Multidimensional Scaling Model for Two-Way One-Mode Continuous Rating Dissimilarity Data

In this paper, we propose a cluster-MDS model for two-way one-mode continuous rating dissimilarity data. The model aims at partitioning the objects into classes and simultaneously representing the cluster centers in a low-dimensional space. Under the normal distribution assumption, a latent class model is developed in terms of the set of dissimilarities in a maximum likelihood framework. In each iteration, the probability that a dissimilarity belongs to each of the blocks conforming to a partition of the original dissimilarity matrix, and the rest of parameters, are estimated in a simulated annealing based algorithm. A model selection strategy is used to test the number of latent classes and the dimensionality of the problem. Both simulated and classical dissimilarity data are analyzed to illustrate the model.     

航线驾驶安全行为多维评价量表的构建

结合现代航线驾驶工作特性及CRM和TEM模型基础上, 通过文献分析、专家访谈和开放式问卷调查, 筛选出现代航线飞行员驾驶安全所必备的27种关键行为特征, 构成中国文化背景下航线驾驶安全行为评价量表的检测项目。对118名中国航线飞行员测评数据的验证性因素分析表明, 由自动化系统认识、领导和管理、情境意识与决策、人际交流与合作技能组成的四维模型优于其他假设模型, 且在四个飞行阶段中均具有良好的信度和结构效度。以其中86名飞行员的安全绩效考核(安全规章、飞行作风、飞行技能和机组管理)数据和飞行员在每个飞行阶段的驾驶安全行为总体表现为效标变量, 以航线驾驶安全行为评价量表四个维度上的驾驶行为特征为预测变量分别进行层次回归分析, 结果表明: 航线驾驶安全行为多维评价量表具有良好的预测效度; 四个维度变量对维护不同飞行阶段的驾驶安全行为分别具有显著的贡献性, 且这种贡献性因飞行阶段的任务不同而有所差异。航线安全驾驶行为多维评价量表的构建, 不仅为航线飞行员安全驾驶行为规范性评估、机组驾驶行为问题诊断以及安全绩效考核提供了一套客观有效的评价工具, 而且也为有针对性的设计航线飞行员选拔模式和有效实施机组人员非技术性技能/CRM训练提供了一个良好的理论基础。     

Internal multidimensional unfolding about a single-ideal—A probabilistic solution

A solution is presented for an internal multidimensional unfolding problem in which all the judgments of a rectangular proximity matrix are a function of a single-ideal object. The solution is obtained by showing that when real and ideal objects are represented by normal distributions in a multidimensional Euclidean space, a vector of distances among a single-ideal and multiple real objects follows a multivariate quadratic form in normal variables distribution. An approximation to the vector's probability density function (PDF) is developed which allows maximum likelihood (ML) solutions to be estimated. Under dependent sampling, the likelihood function contains information about the parametric distances among real object pairs, permitting the estimation of single-ideal solutions and leading to more robust multiple-ideal solutions. Tests for single- vs. multiple-ideal solutions and dependent vs. independent sampling are given. Properties of the proposed model and parameter recovery are explored. Empirical illustrations are also provided.     

Juvenile prostitution and community rehabilitation: an exploratory analysis of beliefs and values

A community, juvenile prostitution rehabilitation programme in Bogotá, Colombia, South America is described; and beliefs and values of the residents were explored. Multiple sorting procedures and multi‐dimensional scaling analysis elicited qualitative, structured, self‐report data, and investigated cognitive constructs. Participants discriminated between belief‐statements along two global dimensions: street‐life and prostitution; and rehabilitation. These were comprised of qualitatively different elements. Clinical implications for interventions with this group and the rehabilitation programme are discussed. Copyright © 2007 John Wiley & Sons, Ltd.     

情绪智力:多维度构思背后的信息

情绪智力作为影响个人发展与领导能力的关键变量已经得到许多关注。虽然许多研究都认为情绪智力更适合从一个多维度变量角度来探讨,但更多研究主要关注情绪智力的整体效应和差异,比较少从情绪智力的单一维度方面来进行研究。本研究以公务员群体来进行分析,运用多元方差分析和结构方程技术来分析人口统计特征对情绪智力多维度构思的影响,并特别关注情绪智力及各维度对个体绩效的影响。最后根据研究结果对与情绪智力相关的理论研究和管理实践提供一些建议。