The 8 "feeling" variables have lower intercorrelations than the "rectangle" variables, created from built-in artificial relationships. So they share less common variance. The term "eigenvalue"--which refers to
the discriminatory power of the factor--is hard to describe
in words. Normally ranging between 0 and Thus, an eigenvalue of 3.47 for the first factor, divided by 8 (variables in this model) = 43.4% of the variance. |
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So for this analysis, three factors accounted for only 77% of the variance among these 8 real "feeling" variables--compared with 98.5% accounted by just two factors for the artificial data. Attention is typically given only to factors with eigenvalues above 1.0. Factors with lower eigenvalues are regarded as analyzing error variance. |