Matrix of associations. The basic unit
of analysis in an EFA is a matrix of associations—either a
correlation or a covariance matrix. If you input a data set into your
EFA, the program will estimate this as step 1. Alternatively, you
can input the correlation or covariance matrix directly, reading it
in as the raw data. This can be useful when trying to replicate someone’s
analyses based on published results or when wanting to analyze ordinal
or dichotomous variables through a corrected correlation matrix (i.e.,
polychoric or tetrachoric). In either case, the extraction methods
above will yield slightly different results based on the matrix of
association being analyzed. The default method in PROC
FACTOR is the simple correlation ...