Factor Analysis as a Classification Method - Factor Loadings
Let us now perform a principal components analysis and look at the two-factor solution. Specifically, let us look at the correlations between the variables and the two factors (or "new" variables), as they are extracted by default; these correlations are also called factor loadings.
STATISTICA FACTOR ANALYSIS |
Factor Loadings (Unrotated) Principal components |
|
Variable | Factor 1 | Factor 2 |
WORK_1 | .654384 | .564143 |
WORK_2 | .715256 | .541444 |
WORK_3 | .741688 | .508212 |
HOME_1 | .634120 | -.563123 |
HOME_2 | .706267 | -.572658 |
HOME_3 | .707446 | -.525602 |
Expl.Var | 2.891313 | 1.791000 |
Prp.Totl | .481885 | .298500 |
Apparently, the first factor is generally more highly correlated with the variables than the second factor. This is to be expected because, as previously described, these factors are extracted successively and will account for less and less variance overall.
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