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. 2023 May 30:1–23. Online ahead of print. doi: 10.3758/s13428-023-02140-2

Table 4.

Exploratory factor analysis – rotated pattern matrix

Task Factor 1 Factor 2 Factor 3 Factor 4 Factor 5
Antisaccade .46 .18 .08 .04 – .03
Visual arrays - color .67 .00 – .03 .14 .14
Visual arrays - concentric .82 – .05 .02 .01 .07
SACT .54 .17 .11 – .06 – .29
Stroop deadline .36 .18 – .09 – .03 – .06
Flanker deadline .30 – .09 – .01 – .12 – .05
Symmetry span – .02 .02 .02 .73 .06
Rotation span .03 .00 .05 .74 – .09
Running span – digits .00 .07 .79 .02 .01
Running span – letters .04 – .09 .77 .04 .04
Raven’s advanced .24 – .06 .07 .19 .41
Letter sets – .04 .24 .26 – .03 .52
Number series .13 .09 .04 .03 .66
Digit comparison .09 .75 – .01 – .01 .06
Letter comparison – .09 .74 .05 .05 .01
Pattern comparison .17 .43 – .18 .24 .13

Extraction done via principal axis factoring; oblimin rotation. The strongest loading for each task is in bolded font. For ease of interpretation, some loadings were multiplied by –1 such that positive loadings reflect better performance on the task was positively related to the factor. Factor correlations were between r = .27 and .42