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• SAS/STAT Procedures A-Z

The FACTOR procedure

• performs a variety of common factor and component analyses and rotations. The methods for factor extraction include:
  • principal component analysis
  • principal factor analysis
  • iterated principal factor analysis
  • unweighted least squares factor analysis
  • maximum likelihood (canonical) factor analysis
  • alpha factor analysis
  • image component analysis
  • Harris component analysis
• provides a variety of methods for prior communality estimation
• input can be multivariate data, a correlation matrix, a covariance matrix, a factor pattern, or a matrix of scoring coefficients
• factor either the correlation or covariance matrix
• can process output from other procedures. For example, it can rotate the canonical coefficients from multivariate analyses in the GLM procedure
• specific methods for orthogonal rotation are:
  • varimax
  • quartimax
  • biquartimax
  • equamax
  • parsimax
  • factor parsimax
  Oblique versions of these methods are also available.
• direct oblique rotations include:
  • quartimin
  • biquartimin
  • covarimin
• general methods for orthogonal rotation include:
  • orthomax with user-specified gamma
  • Crawford-Ferguson family with user-specified weights on variable parsimony and factor parsimony
  • generalized Crawford-Ferguson family with user-specified weights
• general methods for oblique rotation include:
  • direct oblimin with user-specified tau
  • Crawford-Ferguson family with user-specified weights on variable parsimony and factor parsimony
  • generalized Crawford-Ferguson family with user-specified weights
  • promax with user-specified exponent
  • Harris-Kaiser case II with user-specified exponent
  • Procrustes with a user-specified target pattern
• output includes:
  • means
  • standard deviations
  • correlations
  • Kaiser’s measure of sampling adequacy
  • eigenvalues
  • a scree plot
  • eigenvectors
  • prior and final communality estimates
  • the unrotated factor pattern
  • residual and partial correlations
  • the rotated primary factor pattern
  • the primary factor structure
  • interfactor correlations
  • the reference structure
  • reference axis correlations
  • the variance explained by each factor both ignoring and eliminating other factors
  • plots of both rotated and unrotated factors
  • squared multiple correlation of each factor with the variables
  • standard error estimates
  • confidence limits
  • coverage displays
  • scoring coefficients
• obtain separate analyses on observations in groups
• use relative weights for each observation in the input data set
• uses ODS to create a SAS data set corresponding to any table
• uses ODS Graphics to create graphs as part of its output

For further details see the SAS/STAT User's Guide: The FACTOR Procedure
( PDF | HTML )

Examples

• Principal Component Analysis
• Principal Factor Analysis
• Maximum Likelihood Factor Analysis
• Using Confidence Intervals to Locate Salient Factor Loadings

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