Table 1.
Estimated Parameters, Standard Errors, Confidence Intervals, and t Test (or z Test) Statistics for Each Predictor in the Linear (or Beta) Regression Model
Outcomevat0AccuracyRT
Predictorsb (SE) [95% CI]tb (SE) [95% CI]tb (SE) [95% CI]tb (SE)zb (SE) [95% CI]t
Intercept 0.22***(0.05) [0.12 0.31] 4.43, p < .001 padj < .001 1.55***(0.09) [1.36 1.74] 16.47, p < .001 padj < .001 0.77***(0.04) [0.70 0.86] 19.77, p < .001 padj < .001 0.89***(0.16) 5.63, p < .001 padj < .001 1.24***(0.04) [1.15 1.33] 28.95, p < .001 padj < .001
N2ac −0.22*(0.08) [−0.38 −0.06] −2.79, p = .008 padj = .032 −0.32 (0.15) [−0.62 −0.01] −2.10, p = .042 padj = .126 0.08 (0.06) [−0.05 0.21] 1.29, p = 0.203 padj = .407 −1.02***(0.26) −3.93, p < .001 padj < .001 0.08 (0.07) [−0.06 0.22] 1.14, p = .261 padj = .407
ALI −2.52 (6.77) [−16.20 11.16] −0.37, p = .712 padj = 1.067 −10.87 (13.05) [−37.22 15.49] −0.83, p = .410 padj = 1.230 10.18 (5.45) [−0.83 21.19] 1.87, p = .069 padj = .345 −33.48 (21.81) −1.54, p = .124 padj = .499 3.73 (5.94) [−8.27 15.74] 0.63, p = .533 padj = 1.230
Age −0.14*(0.05) [−0.24 −0.04] −2.86, p = .007 padj = .020 −0.07 (0.09) [−0.26 0.12] −0.76, p = .452 padj = .452 0.12*(0.04) [0.03 0.20] 3.00, p = .005 padj = .018 −0.48*(0.16) 3.03, p = .002 padj = .012 0.08 (0.04) [−0.01 0.16] 1.82, p = .075 padj = .151
N2ac*Age −0.16 (0.08) [−0.32 0.00] −2.02, p = .050 padj = .160 −0.11 (0.15) [−0.41 0.20] −0.72, p = .474 padj = .474 0.15 (0.06) [0.03 0.28] 2.44, p = .018 padj = .095 −0.53 (0.26) −2.05, p = .039 padj = .160 0.09 (0.04) [−0.04 0.24] 1.43, p = .160 padj = .319
ALI*Age −4.67 (6.78) [−18.35 9.02] −0.69, p = .495 padj = .965 −10.06 (13.05) [−36.41 16.30] −0.77, p = .445 padj = 1.336 11.23 (5.45) [0.22 22.24] 2.06, p = .046 padj = .229 −15.30 (21.78) −0.70, p = .483 padj = 1.336 9.19 (5.94) [−2.81 21.19] 1.55, p = .130 padj = .519
Adjusted/pseudo-R2 .26 .03 .32 .36 .14
F-statistic F(5, 41) = 4.15, p = .004 F(5, 41) = 1.25, p = .302 F(5, 41) = 5.29, p = .001 – F(5, 41) = 2.46, p = .048
Outcomevat0AccuracyRT
Predictorsb (SE) [95% CI]tb (SE) [95% CI]tb (SE) [95% CI]tb (SE)zb (SE) [95% CI]t
Intercept 0.22***(0.05) [0.12 0.31] 4.43, p < .001 padj < .001 1.55***(0.09) [1.36 1.74] 16.47, p < .001 padj < .001 0.77***(0.04) [0.70 0.86] 19.77, p < .001 padj < .001 0.89***(0.16) 5.63, p < .001 padj < .001 1.24***(0.04) [1.15 1.33] 28.95, p < .001 padj < .001
N2ac −0.22*(0.08) [−0.38 −0.06] −2.79, p = .008 padj = .032 −0.32 (0.15) [−0.62 −0.01] −2.10, p = .042 padj = .126 0.08 (0.06) [−0.05 0.21] 1.29, p = 0.203 padj = .407 −1.02***(0.26) −3.93, p < .001 padj < .001 0.08 (0.07) [−0.06 0.22] 1.14, p = .261 padj = .407
ALI −2.52 (6.77) [−16.20 11.16] −0.37, p = .712 padj = 1.067 −10.87 (13.05) [−37.22 15.49] −0.83, p = .410 padj = 1.230 10.18 (5.45) [−0.83 21.19] 1.87, p = .069 padj = .345 −33.48 (21.81) −1.54, p = .124 padj = .499 3.73 (5.94) [−8.27 15.74] 0.63, p = .533 padj = 1.230
Age −0.14*(0.05) [−0.24 −0.04] −2.86, p = .007 padj = .020 −0.07 (0.09) [−0.26 0.12] −0.76, p = .452 padj = .452 0.12*(0.04) [0.03 0.20] 3.00, p = .005 padj = .018 −0.48*(0.16) 3.03, p = .002 padj = .012 0.08 (0.04) [−0.01 0.16] 1.82, p = .075 padj = .151
N2ac*Age −0.16 (0.08) [−0.32 0.00] −2.02, p = .050 padj = .160 −0.11 (0.15) [−0.41 0.20] −0.72, p = .474 padj = .474 0.15 (0.06) [0.03 0.28] 2.44, p = .018 padj = .095 −0.53 (0.26) −2.05, p = .039 padj = .160 0.09 (0.04) [−0.04 0.24] 1.43, p = .160 padj = .319
ALI*Age −4.67 (6.78) [−18.35 9.02] −0.69, p = .495 padj = .965 −10.06 (13.05) [−36.41 16.30] −0.77, p = .445 padj = 1.336 11.23 (5.45) [0.22 22.24] 2.06, p = .046 padj = .229 −15.30 (21.78) −0.70, p = .483 padj = 1.336 9.19 (5.94) [−2.81 21.19] 1.55, p = .130 padj = .519
Adjusted/pseudo-R2 .26 .03 .32 .36 .14
F-statistic F(5, 41) = 4.15, p = .004 F(5, 41) = 1.25, p = .302 F(5, 41) = 5.29, p = .001 – F(5, 41) = 2.46, p = .048

v, a, t0, and RT denote drift rate, threshold separation, non-decision time, and mean RTs, respectively. SE = standard error, CI = confidence interval. Adjusted R2 is given for linear regression models (v, a, t0, and RT); pseudo-R2 is given for beta-regression (accuracy). p denotes uncorrected p values; padj denotes p values corrected for multiple comparison using a Bonferroni–Holm correction procedure (Holm, 1979). Asterisks denote significant estimates with adjusted p values as *padj < .05, ***padj < .001.

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