Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 0 |
| Since 2007 (last 20 years) | 1 |
Descriptor
Source
| Psychometrika | 5 |
| Educational Measurement:… | 1 |
| International Journal for… | 1 |
| National Center for Research… | 1 |
Author
Publication Type
| Reports - Evaluative | 8 |
| Journal Articles | 7 |
| Speeches/Meeting Papers | 1 |
Education Level
| Elementary Secondary Education | 1 |
| Higher Education | 1 |
Audience
Location
| Greece | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Sidiropoulou-Dimakakou, Despina; Mylonas, Kostas; Argyropoulou, Katerina – International Journal for Educational and Vocational Guidance, 2008
The aim of this study was to describe the hexagonal person-environment fit for the Holland personality types for a Greek sample of 156 university students. The statistical analysis followed both exploratory--such as multidimensional scaling--and confirmatory methods--such as covariance structure models. These methods were employed in an…
Descriptors: Personality Traits, Foreign Countries, College Students, Multidimensional Scaling
Peer reviewedvan Buuren, Stef; Heiser, Willem J. – Psychometrika, 1989
A method based on homogeneity analysis (multiple correspondence analysis or multiple scaling) is proposed to reduce many categorical variables to one variable with "k" categories. The method is a generalization of the sum of squared distances cluster analysis problem to the case of mixed measurement level variables. (SLD)
Descriptors: Cluster Analysis, Mathematical Models, Multidimensional Scaling, Statistical Analysis
Peer reviewedYoung, Forrest W. – Psychometrika, 1981
Alternating least squares and optimal scaling are presented as two approaches to the quantitative analysis of qualitative data. A variety of statistical approaches to this problem are discussed. Three examples are presented. (JKS)
Descriptors: Data Analysis, Goodness of Fit, Hypothesis Testing, Multidimensional Scaling
Peer reviewedSpence, Ian; Lewandowsky, Stephan – Psychometrika, 1989
A method for multidimensional scaling that is highly resistant to the effects of outliers is described. Some Monte Carlo simulations illustrate the efficacy of the procedure, which performs well with or without outliers. (SLD)
Descriptors: Estimation (Mathematics), Mathematical Models, Monte Carlo Methods, Multidimensional Scaling
Peer reviewedTakane, Yoshio – Psychometrika, 1987
Ideal point discriminant analysis (IPDA) is proposed for the analysis of contingency tables of cross-classified data. Several data sets illustrate IPDA, which combines log-linear and dual scaling models to provide a spatial representation of row and column categories and allow statistical evaluation of various structural hypotheses about…
Descriptors: Educational Diagnosis, Goodness of Fit, Mathematical Models, Multidimensional Scaling
Peer reviewedDavison, Mark L. – Psychometrika, 1988
A reparameterization of the general Euclidean model for the external analysis of preference data and a simple least squares method for fitting the model to metric single stimulus data are discussed. The reformulated model is less general than is the earlier formulation by J. D. Carroll (1972). (SLD)
Descriptors: Equations (Mathematics), Estimation (Mathematics), Least Squares Statistics, Multidimensional Scaling
Gierl, Mark J. – Educational Measurement: Issues and Practice, 2005
In this paper I describe and illustrate the Roussos-Stout (1996) multidimensionality-based DIF analysis paradigm, with emphasis on its implication for the selection of a matching and studied subtest for DIF analyses. Standard DIF practice encourages an exploratory search for matching subtest items based on purely statistical criteria, such as a…
Descriptors: Models, Test Items, Test Bias, Statistical Analysis
Ho, Andrew D.; Haertel, Edward H. – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2006
Problems of scale typically arise when comparing test score trends, gaps, and gap trends across different tests. To overcome some of these difficulties, we can express the difference between the observed test performance of two groups with graphs or statistics that are metric-free (i.e., invariant under positive monotonic transformations of the…
Descriptors: Testing Programs, Test Results, Comparative Testing, Multidimensional Scaling

Direct link
