Skip to main content

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