Efficient spatio-temporal data mining with GenSpace graphs

We describe a method for spatio-temporal data mining based on GenSpace graphs. Using familiar calendar and geographical concepts, such as workdays, weeks, climatic regions, and countries, spatio-temporal data can be aggregated into summaries in many ways. We automatically search for a summary with a distribution that is anomalous, i.e., far from user expectations. We repeatedly ranking possible summaries according to current expectations, and then allow the user to adjust these expectations. We also choose a propagation path in the GenSpace subgraph that reduces the storage and time costs of the mining process.     

当代大学生自比型价值观数据的潜在结构

本研究对采自3796名在校大学生的Rokeach Value Survey自比型数据进行了因素分析和多维尺度分析。因素分析从两组价值观选项中分别获得6个双极因素,虽然内容各不相同,但均体现出个人指向-亲社会指向的特点。多维尺度分析所获得的两组选项的2维空间距离分布结果也体现类似特点,结果显示终极性价值观可分为四类,工具性价值观可分为五类。当前大学生价值观中存在着舒适的物质生活、兴奋的生活、幸福、快乐和自尊以及雄心壮志的、勇敢的和诚实的等个人取向内容占优势的可能性。在两种分析方法中,多维尺度分析更适合对自比型价值观数据潜在结构的探究。     

Latent variable modeling in heterogeneous populations

Common applications of latent variable analysis fail to recognize that data may be obtained from several populations with different sets of parameter values. This article describes the problem and gives an overview of methodology that can address heterogeneity. Artificial examples of mixtures are given, where if the mixture is not recognized, strongly distorted results occur. MIMIC structural modeling is shown to be a useful method for detecting and describing heterogeneity that cannot be handled in regular multiple-group analysis. Other useful methods instead take a random effects approach, describing heterogeneity in terms of random parameter variation across groups. These random effects models connect with emerging methodology for multilevel structural equation modeling of hierarchical data. Examples are drawn from educational achievement testing, psychopathology, and sociology of education. Estimation is carried out by the LISCOMP program.Presidential address delivered at the Psychometric Society meetings in Los Angeles, USA and Leuven, Belgium, July 1989. The research was supported by Grant No. SES-8821668 from the National Science Foundation and by Grant No. OERI-G-86-003 from the Office for Educational Research and Improvement, Department of Education. I thank Leigh Burstein, Mike Hollis, Linda Muthén, and Albert Satorra for helpful discussions and Tammy Tam, Jin-Wen Yang, Suk-Woo Kim, and Lynn Short for computational assistance. Designs were created by Arlette Collier, Rita Ling and Jennifer Edic-Bryant.     

Conditions for rasch-dichotomizability of the unidimensional polytomous rasch model

Jansen and Roskam (1986) discussed the compatibility of the unidimensional polytomous Rasch model with dichotomization of the response continuum. They derived a rather strict condition in which dichotomization of multicategory data that fit the unidimensional polytomous Rasch model, results in dichotomous data which fit the dichotomous Research model with effectively the same subject parameter. In this paper a more general dichotomization condition is derived for the polytomous Rasch model, which appears less restrictive, but upholds that the intrinsic logic of the unidimensional polytomous Rasch model defies dichotomization in general. The robustness of dichotomous analysis investigated in a simulation study. It shows a close relation with the two-parameters (Birnbaum) model. Theoretical and methodological implications are discussed.The authors are indebted to H. Müller (personal communication, August 1986), for giving an example which pointed toward the core equation in this paper. The authors also acknowledge the critical comments of Th. Bezambinder and P. Wakker, and of Psychometrika's reviewers to an earlier version of this paper.     

Consumer brand choice: individual and group analyses of demand elasticity

Following the behavior-analytic tradition of analyzing individual behavior, the present research investigated demand elasticity of individual consumers purchasing supermarket products, and compared individual and group analyses of elasticity. Panel data from 80 UK consumers purchasing 9 product categories (i.e., baked beans, biscuits, breakfast cereals, butter, cheese, fruit juice, instant coffee, margarine and tea) during a 16-week period were used. Elasticity coefficients were calculated for individual consumers with data from all or only 1 product category (intra-consumer elasticities), and for each product category using all data points from all consumers (overall product elasticity) or 1 average data point per consumer (interconsumer elasticity). In addition to this, split-sample elasticity coefficients were obtained for each individual with data from all product categories purchased during weeks 1 to 8 and 9 to 16. The results suggest that: 1) demand elasticity coefficients calculated for individual consumers purchasing supermarket food products are compatible with predictions from economic theory and behavioral economics; 2) overall product elasticities, typically employed in marketing and econometric research, include effects of interconsumer and intraconsumer elasticities; 3) when comparing demand elasticities of different product categories, group and individual analyses yield similar trends; and 4) individual differences in demand elasticity are relatively consistent across time, but do not seem to be consistent across products. These results demonstrate the theoretical, methodological, and managerial relevance of investigating the behavior of individual consumers.     

高中生化学问题解决思维过程口语报告编码分析

将高中生化学问题解决思维过程口语报告分为相应的10个行为指标进行人工编码和定量分析。被试是56名高中生,材料为6个中等难度的化学问题,通过“出声思考”实验,记录口语报告,并对口语报告进行编码和数据统计分析,结果发现:(1)高中优生的重复、解释、推理、归纳、总结等行为指标上明显优于中等生;(2)在解决不同类型的化学问题时,重复、设问、推理、归纳和反思等指标存在明显差异;(3)学生能力层次与问题类别在重复、推理、归纳和试误等行为指标上存在明显交互作用。     

Hierarchical classes models for three-way three-mode binary data: interrelations and model selection

Several hierarchical classes models can be considered for the modeling of three-way three-mode binary data, including the INDCLAS model (Leenen, Van Mechelen, De Boeck, and Rosenberg, 1999), the Tucker3-HICLAS model (Ceulemans, Van Mechelen, and Leenen, 2003), the Tucker2-HICLAS model (Ceulemans and Van Mechelen, 2004), and the Tucker1-HICLAS model that is introduced in this paper. Two questions then may be raised: (1) how are these models interrelated, and (2) given a specific data set, which of these models should be selected, and in which rank? In the present paper, we deal with these questions by (1) showing that the distinct hierarchical classes models for three-way three-mode binary data can be organized into a partially ordered hierarchy, and (2) by presenting model selection strategies based on extensions of the well-known scree test and on the Akaike information criterion. The latter strategies are evaluated by means of an extensive simulation study and are illustrated with an application to interpersonal emotion data. Finally, the presented hierarchy and model selection strategies are related to corresponding work by Kiers (1991) for principal component models for three-way three-mode real-valued data.     

Pooling data versus averaging model fits for some prototypical multinomial processing tree models

For a study with multinomial data where there are n_g individuals and with each person having n_r test trials, the question arises as to how to fit the parameters of a multinomial processing tree (MPT) model. Should each parameter be estimated for each individual and then averaged to obtain a group estimate, or should the frequencies in the multinomial categories be pooled so that the model is fit once for the entire group? This basic question is explored with a series of Monte Carlo simulations for some prototypical MPT models. There is a general finding of a pooling advantage for the case where there is a single experimental condition. Also when there are different experimental conditions, there is reduced bias for detecting condition differences for a method based on the pooled data. Although the focus of the paper is on multinomial models, a general theorem is advanced that establishes a basic condition that determines whether there is or is not a difference between the averaging of individual estimates and the estimate based on the pooled data.     

职业评定量表(VIESA)的信度和效度研究

根据D.E.Super的职业发展理论,职业选择的成熟与发展一般分为五个阶段,中学生正处在从探索到成熟的重要转变期。本研究以美国大学测验中心的职业分类系统为基础,以职业评定量表VIESA为工具和对象,对北京市第六十五中学的179名高中三年级学生和北京师范大学心理学系的55名二年级学生进行了施测,检验了量表的信度和效度。量表的信度指标基本在.70以上,构想效度良好,以专业满意感为效标的效标效度达到显著水平。     

Exploratory analysis of contingency tables by loglinear formulation and generalizations of correspondence analysis

Goodman's (1979, 1981, 1985) loglinear formulation for bi-way contingency tables is extended to tables with or without missing cells and is used for exploratory purposes. A similar formulation is done for three-way tables and generalizations of correspondence analysis are deduced. A generalized version of Goodman's algorithm, based on Newton's elementary unidimensional method is used to estimate the scores in all cases.This research was partially supported by National Science and Engineering Research Council of Canada, Grant No. A8724. The author is grateful to the reviewers and the editor for helpful comments.