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What Works Clearinghouse Rating
Vallejo, Guillermo; Livacic-Rojas, Pablo – Multivariate Behavioral Research, 2005
This article compares two methods for analyzing small sets of repeated measures data under normal and non-normal heteroscedastic conditions: a mixed model approach with the Kenward-Roger correction and a multivariate extension of the modified Brown-Forsythe (BF) test. These procedures differ in their assumptions about the covariance structure of…
Descriptors: Computation, Multivariate Analysis, Sample Size, Matrices
Peer reviewedShepard, Roger N. – Psychometrika, 1974
Six major problems confronting attempts to use nonmetric multidimensional scaling to represent structures underlying similarity data are identified and the author's prospects for over-coming each of these problems are presented. (RC)
Descriptors: Cluster Analysis, Comparative Analysis, Data Analysis, Goodness of Fit
Carlson, James E.; Timm, Neil H. – 1980
This paper presents two extensions of the full-rank multivariate linear model that are particularly useful in multivariate analysis of covariance (MANCOVA) and repeated measurements designs. After a review of the basic full-rank model, an extension is described which allows restrictions of a more general nature. This model is useful in the…
Descriptors: Analysis of Covariance, Data Analysis, Hypothesis Testing, Mathematical Formulas
Peer reviewedSirotnik, Kenneth; Wellington, Roger – Journal of Educational Measurement, 1977
A single conceptual and theoretical framework for sampling any configuration of data from one or more population matrices is presented, integrating past designs and discussing implications for more general designs. The theory is based upon a generalization of the generalized symmetric mean approach for single matrix samples. (Author/CTM)
Descriptors: Analysis of Variance, Data Analysis, Item Sampling, Mathematical Models
Peer reviewedCarroll, Robert M. – Educational and Psychological Measurement, 1976
Examines the similarity between the coordinates which resulted when correlations were used as similarity measures and the factor loadings obtained by factor analyzing the same correlation matrix. Real data, a set of error free data, and some computer generated data containing deliberately introduced sampling error are analyzed. (RC)
Descriptors: Comparative Analysis, Correlation, Data Analysis, Factor Analysis
Peer reviewedvan Driel, Otto P. – Psychometrika, 1978
In maximum likelihood factor analysis, there arises a situation whereby improper solutions occur. The causes of those improper solution are discussed and illustrated. (JKS)
Descriptors: Computer Programs, Data Analysis, Factor Analysis, Goodness of Fit
Allison, Patricia A.; Demaerschalk, Dawn; Allison, Derek J. – 1996
The fundamental question in creating coding categories for an open-ended questionnaire is how to transform a complete transcript into manageable pieces of data. This paper describes the methodology involved in coding qualitative data derived from an evaluation of the Cognitive Approaches to School Leadership (CASL) program. The first task was to…
Descriptors: Classification, Coding, Cognitive Processes, Data Analysis
Peer reviewedGower, J. C. – Psychometrika, 1975
Concerned with another form of analysis of m sets of matrices, the Procrustes idea is generalized so that all m sets are simultaneously translated, rotated, reflected and scaled so that a goodness of fit criterion is optimised. A computational technique is given, results of which can be summarized in analysis of variance form. (RC)
Descriptors: Analysis of Variance, Data Analysis, Factor Analysis, Goodness of Fit
Hofman, Richard J. – 1975
In this paper 12 blind transformation procedures are applied to 18 data sets. The results of the analyses indicate that the orthotran transformation solution is not restricted to particular types of data as are so many other transformation solutions. The evidence presented in this paper strongly suggests that the orthotran solution must be…
Descriptors: Data Analysis, Factor Analysis, Factor Structure, Matrices
Peer reviewedTurner, Stephen J.; O'Brien, Gregory – Journal of the American Society for Information Science, 1984
Results of data analysis on 470 journal titles illustrate complexity of the fuzzy set theory modeling process, which consists of three factors--number of missing issues, citations, circulations--and its limitations in making journal binding decisions. Procedures of research, data collection, and data analysis are discussed. Matrices are included.…
Descriptors: Data Analysis, Data Collection, Decision Making, Discriminant Analysis
Peer reviewedEtezadi-Amoli, Jamshid; McDonald, Roderick P. – Psychometrika, 1983
Nonlinear common factor models with polynomial regression functions, including interaction terms, are fitted by simultaneously estimating the factor loadings and common factor scores, using maximum likelihood and least squares methods. A Monte Carlo study gives support to a conjecture about the form of the distribution of the likelihood ratio…
Descriptors: Aphasia, Data Analysis, Estimation (Mathematics), Factor Analysis
Peer reviewedKieft, Raymond N. – College and University, 1977
A methodology for forecasting enrollments at the individual unit level is presented. It can be used to produce detailed enrollment projections (e.g., by class level by semester by year) or more aggregate information (e.g., academic or fiscal year total enrollment), and it does not require the typical institution to obtain new data. (LBH)
Descriptors: Computer Science, Credit Courses, Data Analysis, Educational Planning
Durland, Maryann M. – New Directions for Evaluation, 2005
Although the process of doing social network analysis (SNA) is similar to traditional research and evaluation design, it is in the details that the two traditions diverge. This article describes two areas of differences: (1) the framework for doing SNA; and (2) data collection, analysis, and specific measures. SNA is about relationships and how to…
Descriptors: Network Analysis, Evaluation Methods, Social Networks, Research Methodology
Olson, George H. – 1975
The multivariate general linear hypothesis (MGLH) has received relatively little utilization in educational research and evaluation. This is surprising in view of the fact that recent publications have made the MGLH tractable by practitioners. This paper seeks to stimulate interest in the MGLH by reviewing recent applications, emphasizing the…
Descriptors: Analysis of Covariance, Analysis of Variance, Data Analysis, Educational Research
Beaton, Albert E., Jr. – 1973
Commonality analysis is an attempt to understand the relative predictive power of the regressor variables, both individually and in combination. The squared multiple correlation is broken up into elements assigned to each individual regressor and to each possible combination of regressors. The elements have the property that the appropriate sums…
Descriptors: Algorithms, Computer Programs, Correlation, Data Analysis

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