Abstract
The derivation of multiple and partial regression statistics from uniqueness-augmented factor loadings, presented in the literature for orthogonal factor solutions, is generalized to oblique solutions. A mathematical rationale for the general case, without restriction to uncorrelated factors, is presented. Use of the general formulation is illustrated with a two-factor, seven-variable example.
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References
Dwyer, P. S. The evaluation of multiple and partial correlation coefficients from the factorial matrix.Psychometrika, 1940,5, 211–232.
Dwyer, P. S. The relative efficacy and economy of various test selection methods. PRS Report 957, AGO. 12 June 1952.
Guttman, L. Multiple rectilinear prediction and the resolution into components.Psychometrika, 1940,5, 75–99.
Guttman, L. and Cohen, J. Multiple rectilinear prediction and the resolution into components: II.Psychometrika, 1943,8, 169–183.
Horst. P. (Ed.) The prediction of personal adjustment.SSRC Bull., 1941,48, pp. 437ff.
Thorndike, R. L.Personnel selection. New York: Wiley, 1949.
Thurstone, L. L.Multiple-factor analysis. Chicago: Univ. Chicago Press, 1947.
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This report is based on work done under ARDC Project 7702, in support of the research and development program of the Air Force Personnel and Training Research Center, Lackland Air Force Base, Texas. Permission is granted for reproduction, translation, publication, use, and disposal in whole and in part by or for the United States Government.
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Creager, J.A. General resolution of correlation matrices into components and its utilization in multiple and partial regression. Psychometrika 23, 1–8 (1958). https://doi.org/10.1007/BF02288973
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DOI: https://doi.org/10.1007/BF02288973