1: At this time, there were also extended arguments about whether it was even proper to compute factor scores, due to something called “indeterminacy”—essentially meaning that there are more unknowns than equations being estimated in EFA (for an excellent overview of the issue, see Grice, 2001). The same individuals could be ranked multiple ways, leaving their relative ranking indeterminate. This is a concern that remains today. [return]

2: Refined techniques are actually a bit more complex, taking into account more information than just factor loading—for example, the correlation between factors. However, as the point of this chapter is to discourage the use of factor scores, we will refrain from providing more detail. [return]

3: See the accompanying SAS syntax for this chapter, available on the book website, for a step-by-step example of how SAS computes the factor scores. [return]

4:Keep in mind that others might use the pattern matrix loadings instead of the standardized scoring coefficients when estimating factor scores. See DiStefano et al. (2009) or (Grice, 2001) for more information about these methods. [return]

5: Of course, this sample size is entirely too small, but 10:1 ratio is about average for most EFAs reported in the literature. [return]