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TOOLS >SCALING/DECOMPOSITION > FACTOR ANALYSIS

PURPOSE Perform a complete factor analysis of a 2-mode matrix.
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DESCRIPTION Decomposes a matrix into factors using either principal components or minimum residuals methods.

PARAMETERS
Input dataset.
Name of dataset containing 2-mode matrix to be factored. Data type: Matrix.

Method of factor analysis (Default = Principal Components)
Choices are

Principal Components
Perform a principle component analysis in which the matrix is factored into a product of the most dominant eigenvectors.

Minimum Residuals
Factor the matrix into factors so that the residuals (the sum of squares of the difference between the original data and the product of the factors) are minimized.

Method of factor rotation: (Default = Varimax)
Choices are

None
No rotation is performed

Varimax. Maximizes purity of factors.

Quartimax. Maximizes purity of variables (minimizes loading on multiple factors).Factors are rotated after deleting excess factors (see below).

Minimum Eigenvalue (Default=1.0)
Only factors with eigenvalues greater than the minimum are included up to the number of factors defined below.

Number of factors: (Default=10)
Number of factors into which to decompose the matrix provided they have an eigenvalue greater than the minimum. IMPORTANT NOTE: Factors are rotated after deleting excess factors.

(OUTPUT) Factor Scores: (Default = 'Scores')
Name of file containing the factor scores for each actor on each factor.

Name of file containing the factor loadings for each actor on each factor.

(OUTPUT) Eigenvectors: (Default= 'Eigen')
Name of file containing eigenvalues corresponding to each eigenvector (factor).

(OUTPUT) Factor score coefficients: (Default='Coefs')
Name of file containing the factor coefficients for each actor on each factor.

LOG FILE The log file gives a full set of descriptive statistics of each actors profile. These are followed by the eigenvalues placed in descending order of size and labeled as factors in ascending order. The value of each is expressed as a percentage of the sum and a cumulative percentage of all the factors given so far is presented. The final column gives the ratio of the factor below to the current factor. This is followed by a matrix of factor loadings, entry X(i,j) is the loading of the jth factor on actor i.

TIMING O(N^3)