Table 10.

Results of adjusted 2-sided t-tests comparing the prediction accuracies (RMSE) of 2 different feature selection algorithms: The linear machine learning algorithm partial least squares and the data-driven connectome-based predictive modeling.

PLSR vs. CPM
	Mean (SD)old PLSR	Mean (SD)old CPM	t-statisticold (Cohen’s d)	Mean (SD)young PLSR	Mean (SD)young CPM	t-statisticyoung (Cohen’s d)
Power	0.77 (0.12)	0.77 (0.11)	−1.10 (0.00)	0.77 (0.19)	0.78 (0.18)	−1.97* (0.06)

Note. Power = Power et al’.s graph of putative functional areas, PLSR = partial least squares, CPM = connectome-based predictive modeling, SD = standard deviation.

^*Significant at P = 0.05.