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Karagiannakis, Giannis N.; Baccaglini-Frank, Anna E.; Roussos, Petros – Australian Journal of Learning Difficulties, 2016
Through a review of the literature on mathematical learning disabilities (MLD) and low achievement in mathematics (LA) we have proposed a model classifying mathematical skills involved in learning mathematics into four domains (Core number, Memory, Reasoning, and Visual-spatial). In this paper we present a new experimental computer-based battery…
Descriptors: Mathematics Skills, Mathematical Aptitude, Skill Analysis, Learning Disabilities
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Hendrix, Dean – College & Research Libraries, 2010
This study analyzed 2005-2006 Web of Science bibliometric data from institutions belonging to the Association of Research Libraries (ARL) and corresponding ARL statistics to find any associations between indicators from the two data sets. Principal components analysis on 36 variables from 103 universities revealed obvious associations between…
Descriptors: Bibliometrics, Correlation, Research Libraries, Library Associations
Weiss, David J. – J Counseling Psychol, 1970
Topics discussed include factor analysis versus cluster analysis, analysis of Q correlation matrices, ipsativity and factor analysis, and tests for the significance of a correlation matrix prior to application of factor analytic techniques. Techniques for factor extraction discussed include principal components, canonical factor analysis, alpha…
Descriptors: Cluster Grouping, Correlation, Counseling, Factor Analysis
Hall, Charles E. – 1971
A factor rotation scheme is presented which has a property that is interesting for examining factor-structure hypotheses. Given several clusters of tests the orthogonal bounds scheme produces factors which contain these clusters in some optimal sense. (Author)
Descriptors: Cluster Analysis, Cluster Grouping, Correlation, Factor Analysis
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Paisley, William – Journal of the American Society for Information Science, 1990
Discussion of researchers in the multidisciplinary field of communications focuses on a study using the Social Sciences Citation Index (SSCI) that investigated cocitation frequencies of selected communication researchers and often-cited researchers in related fields. A factor analysis of correlations based on cocitation frequencies is among the…
Descriptors: Authors, Citation Analysis, Cluster Grouping, Communication (Thought Transfer)
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Knapp-Lee, Lisa; Michael, William B. – Educational and Psychological Measurement, 1983
This study (1) provided evidence concerning the construct validity of scales based on the clusters found in a revised, professional-level form of the California Occupational Preference System Interest Inventory and (2) examined the degree of internal consistency of the 16 newly devised subscales. (Author/PN)
Descriptors: Career Planning, Cluster Grouping, Correlation, Factor Analysis
Borko, Harold; And Others – 1968
Experiments were performed to determine the feasibility of using ALCAPP as one form of on-line dialogue. Assuming the ALCAPP (Automatic List Classification and Profile Production) system is in an on-line mode, investigations of those parameters which could affect its stability and reliability were conducted. Fifty-two full test documents were used…
Descriptors: Abstracts, Algorithms, Analysis of Variance, Automation
Shafto, Michael – 1972
The purpose of this paper is to suggest a technique of cluster analysis which is similar in aim to the Interactive Intercolumnar Correlation Analysis (IICA), though different in detail. Two methods are proposed for extracting a single bipolar factor (a "contrast compenent") directly from the initial similarities matrix. The advantages of this…
Descriptors: Bibliographies, Classification, Cluster Analysis, Cluster Grouping
Gray, William M.; Hofmann, Richard J. – 1969
Most responses to educational and psychological test items may be represented in binary form. However, such dichotomously scored items present special problems when an analysis of correlational interrelationships among the items is attempted. Two general methods of analyzing binary data are proposed by Horst to partial out the effects of…
Descriptors: Algorithms, Analysis of Covariance, Cluster Analysis, Cluster Grouping
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Davis, Junius A. – 1965
In this analysis of the structure of the faculty characterizations of students, the same data was used as in the initial study. An oblique solution was obtained by applying the Promax method of Hendrickson and White to the previous Equamax solution. This yielded 18 factors. From intercorrelations among the factor axes, a principal axes procedure…
Descriptors: Cluster Grouping, College Faculty, College Students, Correlation
Sirotnik, Kenneth A. – 1979
This report contains accounts of studies, about scales to be used in the "A Study of Schooling" research project, undertaken to derive indices for constructs presumed to be measureable by composites of items. The report is introduced by a discussion on the rationale for selecting the research methodology used and an explanation of the…
Descriptors: Behavioral Science Research, Cluster Analysis, Cluster Grouping, Correlation
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Davis, Junius A. – 1964
The structure of characterizations of college students by faculty members, particularly observable and significant dimensions or trait patterns, were investigated. Student ratings by faculty members on 80 bi-polar traits, together with Scholastic Aptitude Test (SAT) scores and high school and college freshman average grades, were obtained.…
Descriptors: Academic Achievement, Admission Criteria, Cluster Grouping, College Faculty
Talbott, Albert D. – 1971
The development of Q methodology is briefly reviewed, and the methodology itself is briefly described. Finally, a number of the issues are raised relating to the use of Q. Q methodology can have fruitful applications if it is not used indescriminately. Appropriate use of Q requires careful attention to the way the problems being researched are…
Descriptors: Attitude Measures, Attitudes, Behavioral Science Research, Cluster Grouping
Davis, Junius A. – 1964
This report, a continuation of the study described in TM 000 174 and TM 000 176, employs identical data and similar methods to determine the nature of desirability separate and apart from the rater's perception of the student's academic performance (rather than his actual performance). The results show an absorption in the faculty perception of…
Descriptors: Academic Achievement, Admission Criteria, Cluster Grouping, College Faculty