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| Orthogonal Rotation | 3 |
| Reliability | 3 |
| Factor Analysis | 2 |
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| Item Analysis | 1 |
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| Psychometrika | 2 |
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Peer reviewedten Berge, Jos M. F.; Hofstee, Willem K. B. – Psychometrika, 1999
H. Kaiser (1992) has shown that the sum of coefficients alpha of a set of principal components does not change when the components are transformed by an orthogonal rotation. In this paper, the rotational invariance and the successive alpha-optimality are integrated and generalized in a simultaneous approach. (SLD)
Descriptors: Factor Structure, Orthogonal Rotation, Reliability
Peer reviewedHakstian, A. Ralph – Psychometrika, 1976
Examples are presented in which it is either necessary or desirable to transform two sets of orthogonal axes to simple structure positions by means of the same transformation matrix. A solution is outlined which represents a two-matrix extension of the general "orthomax" orthogonal rotation criterion. (Author/RC)
Descriptors: Factor Analysis, Factor Structure, Matrices, Orthogonal Rotation
Lunneborg, Patricia W. – 1971
This study sought, through a factor analysis of 450 masculine-feminine (MF) items from nine established sources such as the Minnesota Multiphasic Personality Inventory (MMPI), to determine whether in a college sample of 523 students there were a small number of factors common to both sexes, or if the MF scale consisted of so many weak factors that…
Descriptors: College Students, Factor Analysis, Factor Structure, Females


