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Kamdjou, Herve D. Teguim – Open Education Studies, 2023
This article revisits the Mincer earnings function and presents comparable estimates of the average monetary returns associated with an additional year of education across different regions worldwide. In contrast to the traditional Ordinary Least Squares (OLS) method commonly employed in the literature, this study applied a cutting-edge approach…
Descriptors: Outcomes of Education, Artificial Intelligence, Human Capital, Regression (Statistics)
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Hope E. Lackey; Rachel L. Sell; Gilbert L. Nelson; Thomas A. Bryan; Amanda M. Lines; Samuel A. Bryan – Journal of Chemical Education, 2023
The methodology and mathematical treatment of several classic multivariate methods for the analysis of spectroscopic data is demonstrated in a straightforward way that can be used as a basis for teaching an undergraduate introductory course on chemometric analysis. The multivariate techniques of classical least-squares (CLS), principal component…
Descriptors: Chemistry, Data Analysis, Optics, Lighting
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ten Berge, Jos M. F.; Kiers, Henk A. L. – Psychometrika, 1993
R. A. Bailey and J. C. Gower explored approximating a symmetric matrix "B" by another, "C," in the least squares sense when the squared discrepancies for diagonal elements receive specific nonunit weights. A solution is proposed where "C" is constrained to be positive semidefinite and of a fixed rank. (SLD)
Descriptors: Algorithms, Equations (Mathematics), Factor Analysis, Least Squares Statistics
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Morris, John D. – Educational and Psychological Measurement, 1986
An empirical method (PRESS) for examining and contrasting the cross-validated prediction accuracies of some popular algorithms for weighting predictor variables was advanced and examined. The sample specific PRESS method was suggested as most appropriate when selecting among several alternative weighting algorithms to achieve maximum…
Descriptors: Algorithms, Least Squares Statistics, Predictive Measurement, Predictive Validity
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DeSarbo, Wayne S.; And Others – Psychometrika, 1989
A method is presented that simultaneously estimates cluster membership and corresponding regression functions for a sample of observations or subjects. This methodology is presented with the simulated annealing-based algorithm. A set of Monte Carlo analyses is included to demonstrate the performance of the algorithm. (SLD)
Descriptors: Algorithms, Cluster Analysis, Estimation (Mathematics), Least Squares Statistics
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de Leeuw, Jan; Kreft, Ita G. G. – Journal of Educational and Behavioral Statistics, 1995
Practical problems with multilevel techniques are discussed. These problems relate to terminology, computer programs employing different algorithms, and interpretations of the coefficients in either one or two steps. The usefulness of hierarchical linear models (HLMs) in common situations in educational research is explored. While elegant, HLMs…
Descriptors: Algorithms, Computer Software, Definitions, Educational Research
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Tenenhaus, Michel – Psychometrika, 1988
Canonical analysis of two convex polyhedral cones involves looking for two vectors whose square cosine is a maximum. New results about the properties of the optimal solution to this problem are presented. The convergence of an alternating least squares algorithm and properties of limits of calculated sequences are discussed. (SLD)
Descriptors: Algorithms, Analysis of Variance, Graphs, Least Squares Statistics
Morris, John D. – 1986
An empirical method called Predicted Error Sum of Squares (PRESS) is advanced and studied. This method is used to examine the cross-validated prediction accuracies of some popular algorithms for weighted predictor variables. The weighting methods that were considered were ordinary least squares, ridge regression, regression on principal…
Descriptors: Algorithms, Least Squares Statistics, Measurement Techniques, Minicomputers
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Bijleveld, Catrien C. J. H.; de Leeuw, Jan – Psychometrika, 1991
An alternating least squares method for iteratively fitting the longitudinal reduced-rank regression model is proposed. For social and behavioral science applications, the developed algorithm does not rely on the assumption of multinomial errors and allows for scaling of input and output variables. (SLD)
Descriptors: Algorithms, Behavioral Science Research, Cross Sectional Studies, Equations (Mathematics)