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Morris, John D.; Huberty, Carl J. – Multivariate Behavioral Research, 1987
The cross-validated classification accuracies of three predictor weighting strategies (least squares, ridge regression, and reduced rank) were compared under varying simulated data conditions for the two-group classification problem. Results were somewhat similar to previous findings with multiple regression when absolute rather than relative…
Descriptors: Algorithms, Multiple Regression Analysis, Predictor Variables, Simulation
Groen, Guy J. – 1974
This paper presents the results of three experiments studying routine problem-solving tasks in simple addition and subtraction. Indications are that children tend to solve such problems by internalized counting procedures which may be learned independently as a consequence of practice in problem solving. Brief descriptions of exploratory studies…
Descriptors: Addition, Algorithms, Elementary School Mathematics, Mathematics Education
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
Mayeske, George W.; Beaton, Albert E., Jr. – 1974
The results of an algorithm which is designed to take a set of commonality coefficients, either real or manipulated, and, if possible, produce one or more sets of regressor correlations that are consistent with them are examined. A number of different ways of resolving the higher order commonality values into their lower orders were tried and the…
Descriptors: Algorithms, Computer Programs, Correlation, Mathematical Applications
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