A General Framework for Multivariate Analysis with Optimal Scaling: The R Package aspect

In a series of papers De Leeuw developed a general framework for multivariate analysis with optimal scaling. The basic idea of optimal scaling is to transform the observed variables (categories) in terms of quantifications. In the approach presented here the multivariate data are collected into a multivariable. An aspect of a multivariable is a function that is used to measure how well the multivariable satisfies some criterion. Basically we can think of two different families of aspects which unify many well-known multivariate methods: Correlational aspects based on sums of correlations, eigenvalues and determinants which unify multiple regression, path analysis, correspondence analysis, nonlinear PCA, etc. Non-correlational aspects which linearize bivariate regressions and can be used for SEM preprocessing with categorical data. Additionally, other aspects can be established that do not correspond to classical techniques at all. By means of the R package aspect we provide a unified majorization-based implementation of this methodology. Using various data examples we will show the flexibility of this approach and how the optimally scaled results can be represented using graphical tools provided by the package.

An Urban Management Performance Modeling Via Evaluation Using Improved Green Balanced Score Cards And Fuzzy DEMATEL Under Uncertainty Solving By A New Compromised Method Based On TOPSIS And VIKOR

Environmental awareness is one of the most important issues that in which general public interest are growing rapidly, especially in the industrialized countries. Some trends that can be clearly seen these days are: the number of members/financial contributors of various environmental preservation societies and associations are increasing dramatically, the amount of legislation related to environmental protection both nationally and at a super-national. The number of recycling and reuse schemes, both in industry and privately is on the rise and most people engage in one or more such programs, Unnatural climate effects suspected to stem from pollution have increased and receive much media attention and so on. This means that it is becoming increasingly more important for an enterprise to be able to manage its operations in a way that minimize the negative environmental impact they might result in, directly or indirectly. At the same time, it is a fact that you can't manage what you can't measure. Thus, performance measurement is a key element in enabling performance management, performance improvement and performance documentation. When combining the pivotal importance of environmental friendliness with the need for performance measurement, we'll face with concept of green performance measurement, an area that has been largely neglected as a pure source of competitive advantages. The balanced scorecard is one of the performance evaluating tools that empower in this research by using of decision making technics and can be used to green performance evaluation. In this thesis, we proposed an urban management performance modeling via evaluation using improved Green Balanced Score Cards and fuzzy DEMATEL under uncertainty solving by a new compromised method based on TOPSIS and VIKOR simultaneously. Keywords: Green performance evaluation, balanced scorecard card, MCDM technics, Fuzzy, new compromised solution method

A psychometric modeling approach to fuzzy rating data

Modeling fuzziness and imprecision in human rating data is a crucial problem in many research areas, including applied statistics, behavioral, social, and health sciences. Because of the interplay between cognitive, affective, and contextual factors, the process of answering survey questions is a complex task, which can barely be captured by standard (crisp) rating responses. Fuzzy rating scales have progressively been adopted to overcome some of the limitations of standard rating scales, including their inability to disentangle decision uncertainty from individual responses. The aim of this article is to provide a novel fuzzy scaling procedure which uses Item Response Theory trees (IRTrees) as a psychometric model for the stage-wise latent response process. In so doing, fuzziness of rating data is modeled using the overall rater's pattern of responses instead of being computed using a single-item based approach. This offers a consistent system for interpreting fuzziness in terms of individual-based decision uncertainty. A simulation study and two empirical applications are adopted to assess the characteristics of the proposed model and provide converging results about its effectiveness in modeling fuzziness and imprecision in rating data

Perceived features and similarity of images: An investigation into their relationships and a test of Tversky's contrast model.

The creation, storage, manipulation, and transmission of images have become less costly and more efficient. Consequently, the numbers of images and their users are growing rapidly. This poses challenges to those who organize and provide access to them. One of these challenges is similarity matching. Most current content-based image retrieval (CBIR) systems which can extract only low-level visual features such as color, shape, and texture, use similarity measures based on geometric models of similarity. However, most human similarity judgment data violate the metric axioms of these models. Tversky's (1977) contrast model, which defines similarity as a feature contrast task and equates the degree of similarity of two stimuli to a linear combination of their common and distinctive features, explains human similarity judgments much better than the geometric models. This study tested the contrast model as a conceptual framework to investigate the nature of the relationships between features and similarity of images as perceived by human judges. Data were collected from 150 participants who performed two tasks: an image description and a similarity judgment task. Qualitative methods (content analysis) and quantitative (correlational) methods were used to seek answers to four research questions related to the relationships between common and distinctive features and similarity judgments of images as well as measures of their common and distinctive features. Structural equation modeling, correlation analysis, and regression analysis confirmed the relationships between perceived features and similarity of objects hypothesized by Tversky (1977). Tversky's (1977) contrast model based upon a combination of two methods for measuring common and distinctive features, and two methods for measuring similarity produced statistically significant structural coefficients between the independent latent variables (common and distinctive features) and the dependent latent variable (similarity). This model fit the data well for a sample of 30 (435 pairs of) images and 150 participants (χ2 =16.97, df=10, p = .07508, RMSEA= .040, SRMR= .0205, GFI= .990, AGFI= .965). The goodness of fit indices showed the model did not significantly deviate from the actual sample data. This study is the first to test the contrast model in the context of information representation and retrieval. Results of the study are hoped to provide the foundations for future research that will attempt to further test the contrast model and assist designers of image organization and retrieval systems by pointing toward alternative document representations and similarity measures that more closely match human similarity judgments

Social axioms: A new culture measure for South African business research

This study is intended to introduce social axiom theory to South African business researchers and, in this process, to provide new empirical evidence pertinent to the South African context. We examine social axioms in the largest and most representative national metropolitan population ever studied, providing scores for social axiom dimensions at the individual-level and nation-level, as well as assessments of relations with sociodemographics, values, personality and life satisfaction. The results support the convergent validity, discriminant validity and composite reliability of the 25-item brief version of the Social Axioms Scale. We extend prior research on social axioms and personality by examining relations with optimum stimulation level (OSL), an important personality construct studied in marketing and human resource management. A hierarchical regression model illustrates the power of social axioms in predicting life satisfaction, over and above the effects of sociodemographics, values and optimum stimulation level. Several points of departure for fruitful business research are identified

Tag Clouds: How format and categorical structure affect categorization judgment

This paper examines how category judgments are influenced by categorical structure and the formatting of tag clouds. Despite the enormous research on categorization, little research has been directed at investigating whether one person can recognize another's categorical structure. A novel approach to measure similarity and categorical structure is proposed. This approach involves the use of latent semantic analyses to compute semantic distances between category exemplars. The empirical domain will be tag clouds, a new development in social computing that provides a particularly useful paradigm for investigating how people identify the categorical structures of others. Three experiments examine how categorical structure and different formatting styles used in tag clouds might affect categorization. Findings reveal that categorization judgments are influenced by categorical structure and tighter structures result in higher accuracy. Format variables such as font size and sorting order were also found to influence accuracy. Future experimental directions are detailed

Rethinking cognitive style in psychology

Bibliography: leaves 240-257.This thesis proposes to answer a single question: do the stylistic features of cognition operate independently of cognitive contents? The question itself has a history, and the way it has been framed, and the types of answers it has attracted have been related to ideological and political interests. Chapter 1 reviews four social psychological theories of the relationship between cognitive style and ideological beliefs - authoritarianism, extremism theory, context theory, and value pluralism theory. It argues that these (empiricist) accounts have been bedeviled by a tension between theoretical universalism and political critique, and have fostered the view that cognitive traits are stable, general, and pervasive properties of individual psychology. Chapter 2 focuses on the construct of intolerance of ambiguity, and shows how - in the manner of Danziger's (1985) "methodological circle" - universalistic assumptions have become incorporated into measurement instruments; and how all evidence of individual variability in cognitive style has been accommodated by interactionist models of personality, leaving the empiricist view intact. Roy Bhaskar's critical realism is used as an alternative to a empiricist psychology, and Michael Billig's rhetorical psychology is used as an alternative to universalistic theories of cognitive style. A measurement procedure is developed which can assess cross-content variability in ambiguity tolerance. Three studies are performed in order to justify a move towards an anti-universalistic conception of cognitive style. Study l evaluates the hypothesized generality of ambiguity tolerance on a sample of university students. Factor analysis and correlational matrices show that ambiguity tolerance toward different authorities is domain specific, and that different factors are related to each other positively, negatively, and orthogonally. Study 2 employs the same sample, and uses polynomial regression analysis to show that the relationship between ambiguity tolerance and ideological conservatism is highly variable across content domain. Study 3 replicates these central findings with another student sample and with different scale contents. The results of all three studies arc contrary to the predictions of the social psychological accounts of cognitive style. They show that expressions of cognitive style are context- and content-dependent, and suggest that the empiricist "thing-like" ontology be replaced with a praxis- and concept-dependent ontology