Relationships between two systems of factor analysis
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Considering only population values, it is shown that the complete set of factors of a correlation matrix with units in the diagonal cells may be transformed into the factors derived by factoring these correlations with communalities in the diagonal cells. When the correlations are regarded as observed values, the common factors derived as a transformation of the complete set of factors of the correlation matrix with units in the diagonal cells satisfy Lawley's requirement for a maximum likelihood solution and are a first approximation to Rao's canonical factors.
KeywordsPublic Policy Correlation Matrix Statistical Theory Common Factor Canonical Factor
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- 1.Guttman, Louis. General theory and methods for matrix factoring.Psychometrika, 1944,9, 1–16.Google Scholar
- 2.Guttman, Louis. Some necessary conditions for common-factor analysis.Psychometrika, 1954,19, 149–61.Google Scholar
- 3.Harris, Chester W. Separation of data as a principle in factor analysis.Psychometrika, 1955,20, 23–28.Google Scholar
- 4.Holzinger, Karl J. Factoring test scores and implications for the method of averages.Psychometrika, 1944,9, 155–67.Google Scholar
- 5.Lawley, D. N. The estimation of factor loadings by the method of maximum likelihood.Proc. Royal Soc. Edinburgh, 1940,60, 64–82.Google Scholar
- 6.Lawley, D. N. Further investigations in factor estimation.Proc. Royal Soc. Edinburgh, 1941,61, 176–85.Google Scholar
- 7.Rao, C. R. Estimation and tests of significance in factor analysis.Psychometrika, 1955,20, 93–111.Google Scholar
- 8.Rippe, Dayle D. Application of a large sampling criterion to some sampling problems in factor analysis.Psychometrika, 1953,18, 191–205.Google Scholar