Application of model-selection criteria to some problems in multivariate analysis

A review of model-selection criteria is presented, with a view toward showing their similarities. It is suggested that some problems treated by sequences of hypothesis tests may be more expeditiously treated by the application of model-selection criteria. Consideration is given to application of model-selection criteria to some problems of multivariate analysis, especially the clustering of variables, factor analysis and, more generally, describing a complex of variables.     

达尔文医学的哲学启示

达尔文医学从本源上阐明队类疾病产生的偶然性与必然性的对立统一。其对进化论的重新反思和认识,具有重要的人文价值和现实意义。     

Stepwise variable selection in factor analysis

It is very important to choose appropriate variables to be analyzed in multivariate analysis when there are many observed variables such as those in a questionnaire. What is actually done in scale construction with factor analysis is nothing but variable selection.In this paper, we take several goodness-of-fit statistics as measures of variable selection and develop backward elimination and forward selection procedures in exploratory factor analysis. Once factor analysis is done for a certain numberp of observed variables (thep-variable model is labeled the current model), simple formulas for predicted fit measures such as chi-square, GFI, CFI, IFI and RMSEA, developed in the field of the structural equation modeling, are provided for all models obtained by adding an external variable (so that the number of variables isp + 1) and for those by deleting an internal variable (so that the number isp – 1), provided that the number of factors is held constant.A programSEFA (Stepwise variable selection in Exploratory Factor Analysis) is developed to actually obtain a list of the fit measures for all such models. The list is very useful in determining which variable should be dropped from the current model to improve the fit of the current model. It is also useful in finding a suitable variable that may be added to the current model. A model with more appropriate variables makes more stable inference in general.The criteria traditionally often used for variable selection is magnitude of communalities. This criteria gives a different choice of variables and does not improve fit of the model in most cases.The URL of the programSEFA is http://koko15.hus.osaka-u.ac.jp/~harada/factor/stepwise/.     

制约研究生科研选题的几点因素

研究生的科研选题的意义是十分重要的,除了作为培养未来的科研人才的一条有效途径以外,研究生的科研方向代表着目前各研究领域的最基础部分,但是,由于学生自身的各种主观因素以及学校和社会的多种客观因素导致了目前的局面：只有好的愿望达不到好的目的。要推动整个社会的科技进步,需要更深入更长远对人才的培养问题进一步思考。     

社会网络视角下的同伴关系与心理健康

近年来, 从社会网络视角考察同伴关系与心理健康的相互作用正成为发展心理学和健康心理学研究的热点。研究者多借助整体网和纵向数据, 通过两种作用机制, 即选择过程(selection process) (强调心理和行为变量对社会网络和同伴关系的影响, 如关系的形成、维持和解除)和影响过程(influence process) (强调社会网络和同伴关系对心理和行为变量的影响), 来分析同伴关系与心理健康协同演进的动态过程。实证研究关注的领域集中在青少年健康风险行为(如吸烟、喝酒、药物滥用)和情绪问题(如抑郁、焦虑、孤独感)。未来研究应该注重拓展社会网络的类型和样本、加强理论建构、增加对积极心理和消极关系的研究, 并有望在互联网领域及社会网络的生物学基础等方面取得进展。     

Principles for Designing Randomized Preventive Trials in Mental Health: An Emerging Developmental Epidemiology Paradigm

An emerging population-based paradigm is now being used to guide the design of preventive trials used to test developmental models. We discuss elements of the designs of several ongoing randomized preventive trials involving reduction of risk for children of divorce, for children who exhibit behavioral or learning problems, and for children whose parents are being treated for depression. To test developmental models using this paradigm, we introduce three classes of design issues: design for prerandomization, design for intervention, and design for postintervention. For each of these areas, we present quantitative results from power calculations. Both scientific and cost implications of these power calculations are discussed in terms of variation among subjects on preintervention measures, unit of intervention, assignment, balancing, number of pretest and posttest measures, and the examination of moderation effects.     

SOCIAL VALIDATION: THE EVOLUTION OF STANDARDS OF COMPETENCY FOR TARGET BEHAVIORS

The use of social validation procedures has become widespread in recent years. Although most researchers have used social validation procedures to select target behaviors and to evaluate whether the changes produced by a treatment program should be considered socially useful, little attention has been focused upon using the social validation process to determine the optimal levels for target behaviors. This paper suggests several ways in which social validation procedures can be employed in order to select when and how much to change target behaviors.     

TEACHING RETARDED WOMEN A CLOTHING SELECTION SKILL USING COMMUNITY NORMS

Five institutionalized retarded women were taught a clothing selection skill to coincide with popular fashion. Normative data concerning popular styles of color-coordinated clothing were collected through observations of women's apparel in a local community. Using a puzzle simulation of a woman with alternative pieces of colored clothing, color coordination training was conducted using modelling, instructions, practice, praise, and feedback to teach popular selections of color combinations. A generalization training component with actual clothing was also included. Training was accompanied by large increases in percentage of popular color selections with the puzzle and actual clothing. The increases maintained over a seven- to 14-week followup period. Time efficiency measures supported the use of the simulation procedure as opposed to total reliance on actual clothing. The results underscore the utility of local norms in community preparation programs and the efficacy of instructional procedures for severely and profoundly retarded persons as part of their participation in the deinstitutionalization movement.