When SPSS performs a principal components analysis using a direct oblimin rotation it produces three matrices of loadings. A component matrix of initial unrotated loadings, a structure matrix of item-factor correlations and a pattern matrix of standardised regression coefficients between each factor and each item. For reporting purposes http://lists.asu.edu/cgi-bin/wa?A2=ind0312&L=aera-d&T=0&F=&S=&P=7624 suggests using the pattern matrix, in this situation, as it partials out the effects of other items on each factor.
Factor Loading |
Sample Size needed for significance |
|
0.30 |
350 |
|
0.35 |
250 |
|
0.40 |
200 |
|
0.45 |
150 |
|
0.50 |
120 |
|
0.55 |
100 |
|
0.60 |
85 |
|
0.65 |
70 |
|
0.70 |
60 |
|
0.75 |
50 |