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A NEW MATRIX FOR THE ASSESSMENT OF FACTOR CONTRIBUTIONS
Multivariate Behavioral Research
|January 30, 2016
Summary
A novel factor contribution matrix, derived from initial factor loadings and an orthonormal transformation, is proposed. This matrix effectively evaluates factor contributions to variables and can replace primary factor patterns in oblique simple structure analysis.
Area of Science:
- Multivariate statistics
- Factor analysis
Background:
- Evaluating factor contributions to variables is crucial in multivariate analysis.
- Existing methods for assessing oblique simple structure have limitations.
Purpose of the Study:
- To introduce a new matrix for evaluating factor contributions.
- To demonstrate the utility of this matrix in assessing oblique simple structure.
Main Methods:
- The proposed method involves calculating the matrix product of the initial factor loading matrix and the least-squares orthonormal approximation to the general oblique transformation matrix.
- This new matrix is termed the factor contribution matrix.
Main Results:
- The factor contribution matrix is identified as the most adequate for evaluating factor contributions to variables.
- The factor contribution matrix can effectively replace the primary factor pattern matrix when evaluating oblique simple structure.
Conclusions:
- The proposed factor contribution matrix offers a more robust method for analyzing factor contributions.
- This approach enhances the evaluation of oblique simple structure in factor analysis.
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