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| Multiple Regression Analysis | 3 |
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| Analysis of Variance | 1 |
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| McDonald, Roderick P. | 3 |
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Peer reviewedMcDonald, Roderick P.; And Others – Psychometrika, 1979
Problems in avoiding the singularity problem in analyzing matrices for optimal scaling are addressed. Conditions are given under which the stationary points and values of a ratio of quadratic forms in two singular matrices can be obtained by a series of simple matrix operations. (Author/JKS)
Descriptors: Factor Analysis, Matrices, Measurement, Multiple Regression Analysis
Peer reviewedMcDonald, Roderick P. – Psychometrika, 1978
The relationship between the factor structure of a convariance matrix and the factor structure of a partial convariance matrix when one or more variables are partialled out of the original matrix is given in this brief note. (JKS)
Descriptors: Analysis of Covariance, Correlation, Factor Analysis, Factor Structure
Peer reviewedMcDonald, Roderick P. – Multivariate Behavioral Research, 1979
Two major and two minor principles are shown to serve to generate a large number of multivariate models, including canonical analysis, factor analysis, and latent trait test theory. The statistical underpinnings of the theory are discussed. (Author/JKS)
Descriptors: Analysis of Variance, Data Analysis, Factor Analysis, Mathematical Models
