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Lei, Wu; Qing, Fang; Zhou, Jin – International Journal of Distance Education Technologies, 2016
There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…
Descriptors: Causal Models, Attribution Theory, Correlation, Evaluation Methods
Goff, Peter; Salisbury, Jason; Blitz, Mark – Wisconsin Center for Education Research, 2015
Initiatives to increase leadership accountability coupled with efforts to promote data-driven leadership have led to widespread adoption of instruments to assess school leaders. In this paper we present a decision matrix that practitioners and researchers can use to facilitate instrument selection. Our decision matrix focuses on the psychometric…
Descriptors: Comparative Analysis, Measures (Individuals), Feedback (Response), Psychometrics
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Rushton, J. Philippe; Cvorovic, Jelena; Bons, Trudy Ann – Intelligence, 2007
To examine whether the Roma (Gypsy) population of Serbia, like other South Asian population groups, average lower than Europeans on "g", the general factor of intelligence, we tested 323 16- to 66-year-olds (111 males; 212 females) in three different communities over a two-year-period on the Raven's Colored and/or Standard Progressive…
Descriptors: Cognitive Ability, Foreign Countries, Intelligence, Ethnic Groups
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Krus, David J.; Weiss, David J. – Multivariate Behavioral Research, 1976
Results of empirical comparisons of an inferential model of order analysis with factor analytic models were reported for two sets of data. On the prestructured data set both order and factor analytic models returned its dimensions of length, width and height, but on the random data set the factor analytic models indicated the presence of…
Descriptors: Comparative Analysis, Data Analysis, Factor Analysis, Mathematical Models
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McQuitty, Louis L.; Koch, Valerie L. – Educational and Psychological Measurement, 1975
A rapid method for hierarchically clustering the n objects of a matrix which portrays the interrelation of every object to every other object, where n equals any number up to 1,000 and even larger, is developed and discussed. Results compare favorably with those from other excellent methods. (Author/BJG)
Descriptors: Cluster Analysis, Comparative Analysis, Evaluation Methods, Matrices
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McQuitty, Louis L.; Koch, Valerie L. – Educational and Psychological Measurement, 1976
A relatively reliable and valid hierarchy of clusters of objects is plotted from the highest column entries, exclusively, of a matrix of interassociations between the objects. Having developed out of a loose definition of types, the method isolates both loose and highly definitive types, and all those in between. (Author/RC)
Descriptors: Cluster Analysis, Cluster Grouping, Comparative Analysis, Data Analysis
Rim, Eui-Do – 1975
A stepwise canonical procedure, including two selection indices for variable deletion and a rule for stopping the iterative procedure, was derived as a method of selecting core variables from predictors and criteria. The procedure was applied to simulated data varying in the degree of built in structures in population correlation matrices, number…
Descriptors: Analysis of Variance, Comparative Analysis, Correlation, Factor Analysis
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Lomax, Richard G.; Algina, James – Journal of Educational Measurement, 1979
Results of using multimethod factor analysis and exploratory factor analysis for the analysis of three multitrait-multimethod matrices are compared. Results suggest that the two methods can give quite different impressions of discriminant validity. In the examples considered, the former procedure tends to support discrimination while the latter…
Descriptors: Comparative Analysis, Factor Analysis, Goodness of Fit, Matrices
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Rudnitsky, Alan N. – 1977
Three approaches to the graphic representation of similarity and dissimilarity matrices are compared and contrasted. Specifically, Kruskal's multidimensional scaling, Johnson's hierarchical clustering, and Waern's graphing techniques are employed to depict, in two dimensions, data representing the structure of a set of botanical concepts. Each of…
Descriptors: Botany, Cluster Analysis, Cluster Grouping, Comparative Analysis
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Ray, Michael L.; Heeler, Roger M. – Educational and Psychological Measurement, 1975
Methods for analyzing the multitrait-multimethod matrix are reviewed and the results of their application to a classic data set are compared. It is shown that different analysis methods can yield different validity conclusions, and that the results obtained are partly dependent on the subjective judgments of the users. (Author/RC)
Descriptors: Cluster Analysis, Comparative Analysis, Factor Analysis, Goodness of Fit
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Leutner, Detlev; Weinsier, Philip D. – Computers in Human Behavior, 1994
This article's goals are to validate the Computer and Information Technology Attitude Inventory (Weinsier and Leutner, 1988), a nontraditional approach to attitude measurement; and to report on a study designed to search for intercultural differences or cross-cultural consistency of attitudes toward computers and information technology. (46…
Descriptors: Attitude Measures, College Students, Comparative Analysis, Computer Anxiety