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Table 2 Multiple regression models

From: Measurement of individual differences in face-identity processing abilities in older adults

CFMT
   b SE(b) t(136) p R Corr.R2 p
OA
M1 SA − 0.12 0.09 − 1.21 0.22    
  MR 0.00 0.10 − 0.05 0.95    
  FI 0.20 0.10 1.87 0.06 .06 .03 .09
M2 GFMT*** 0.33 0.09 3.43 < .001    
  HP − 0.06 0.09 − 0.65 0.51 .10 .08 < .01
YA
M1 SA 0.05 0.08 0.67 .50    
  MR** 0.27 0.08 3.07 < .01    
  FI* − 0.17 0.08 − 2.03 < .05 .07 .05 < .05
M2 GFMT*** 0.40 0.07 4.96 < .001    
  HP 0.08 0.13 1.03 .30 .18 .17 < .001
GFMT
   b SE(b) t(97) p R Corr.R2 p
OA
M1 SA − 0.00 0.09 − .007 0.99    
  MR 0.14 0.09 1.49 0.13    
  FI*** 0.36 0.10 3.67 < .001 .20 .17 < .001
M2 CFMT*** 0.31 0.09 3.43 < .001    
  HP* 0.21 0.09 2.35 < .05 .15 .13 < .001
YA
M1 SA − 0.02 0.08 − 0.23 .81    
  MR* 0.22 0.08 2.55 < .05    
  FI − 0.01 0.08 − 0.18 .85 .04 .02 .07
M2 CFMT*** 0.39 0.07 5.10 < .001    
  HP* 0.15 0.07 2.00 < .05 .20 .19 < .001
  1. The table shows standardized (b) coefficients with their standard errors, t—statistic with significance level, multiple correlation coefficient, and determination coefficient. ΔCorr.R2 is the change in corr. R2 when a further covariate enters the model. M1 Model 1, M2 Model 2, CFMT Cambridge Face Memory Test, GFTM Glasgow Face Matching Test, HP Holistic Processing, SA Selective Attention, MR Mental Rotation, FI Fluid Intelligence