coefficients you see that both the centered Hassles and the interaction terms are signifi-
cant (p 5 .000 and .037, respectively), but the social support variable is not significant.
By convention we leave it in our regression solution, because it is involved in the inter-
action, even though the associated tvalue shows that deleting that variable would not
lead to a significant decrease in R^2.
Our regression equation now becomes
YN 5 .086 chassles 1 .146 csupport – .005 chassupp 1 89.585.
15.14 Mediating and Moderating Relationships 559
Hassles
1.000
–.167
.577**
.910**
1.000**
–.167
–.297*
Hassles
Support
Symptoms
hassupp
chassles
csupport
chassupp
Support
–.167
1.000
–.134
–.510**
–.167
1.000**
.402**
Symptoms
.577**
–.134
1.000
.585**
.577**
–.134
–.391**
hassupp
.910**
–.510**
.585**
1.000
.910**
–.510**
–.576**
chassles
1.000**
–.167
.577**
.910**
1.000
–.167
–.297*
csupport
–.167
1.000**
–.134
–.510**
–.167
1.000
.402**
chassupp
–.297*
.402**
–.391**
–.576**
–.297*
.402**
1.000
Correlations
Pearson Correlation
** Correlation is significant at the .01 level (2-tailed).
* Correlation is significant at the .05 level (2-tailed).
Sum of
Squares
9427.898
14839.816
24267.714
Model
1 Regression
Residual
Total
df
3
52
55
Mean
Square
3142.633
285.381
F
11.012
Sig.
.000a
ANOVAb
Coefficientsa
Model
1 (Constant)
chassles
csupport
chassupp
B
89.585
8.594E-02
.146
–5.06E-03
Std. Error
2.292
.019
.305
.002
Beta
.509
.057
–.262
t
30.094
4.473
.479
–2.144
Sig.
.000
.000
.634
.037
Unstandardized
Coefficients
Standardized
Coefficients
aPredictors: (Constant), chassupp, chassles, csupport
bDependent Variable: Symptoms
aDependent Variable: Symptoms
Table 15.5 Regression solution for moderated relationship between hassles
and symptoms
R
.623a
Model
1
R Square
.388
Adjusted
R Square
.353
Std. Error
of the
Estimate
16.8932
Model Summary
aPredictors: (Constant), CHASSUPP, CHASSLES, CSUPPORT