Help interpret Moderation (Macro Hayes) results

Posted by psy_vm on May 18, 2014; 9:30pm
URL: http://spssx-discussion.165.s1.nabble.com/Help-interpret-Moderation-Macro-Hayes-results-tp5726125.html

Hello,

I need help interpreting my results for moderation/interaction effect. I'll discuss one result here which can be as a guideline for 15 other macros that I need to run. I've run Hayes process for moderaion in SPSS for finding moderation effect.
My I.V. is group membership, categorical with 2 groups
My D.V. is depression level, continuous. I have 5 different variables so running macro 1 by 1 for all of them.
My moderating variable is Resilience level,continuous. I have 2 more moderating variables and will run macros separately for them. in total 1 I.V x 3 modrators x 5 D.V.s = 15 macros.

Please help me understand and interpret my results, including test of simple slopes, un/standardized figures, and other important aspects.

Also, please direct me to an online resource for understanding these results.
Thanks in advance!
*********.
Model = 1
    Y = qoltot
    X = VisaGrou
    M = bcope_ma

Sample size
         97

**************************************************************************
Outcome: qoltot

Model Summary
          R       R-sq          F        df1        df2          p
      .5083      .2584    10.9638     3.0000    93.0000      .0000

Model
              coeff         se          t          p       LLCI       ULCI
constant    68.8666     1.7854    38.5717      .0000    65.3211    72.4121
bcope_ma     -.7737      .3217    -2.4048      .0182    -1.4125     -.1348
VisaGrou   -12.1130     3.5872    -3.3767      .0011   -19.2366    -4.9895
int_1        1.0766      .6546     1.6445      .1034     -.2234     2.3765

Interactions:

 int_1    VisaGrou    X     bcope_ma

*************************************************************************

Conditional effect of X on Y at values of the moderator(s):
   bcope_ma     Effect         se          t          p       LLCI       ULCI
    -5.9635   -18.5331     4.8543    -3.8179      .0002   -28.1727    -8.8934
      .0000   -12.1130     3.5872    -3.3767      .0011   -19.2366    -4.9895
     5.9635    -5.6930     5.7143     -.9963      .3217   -17.0406     5.6546

Values for quantitative moderators are the mean and plus/minus one SD from mean.
Values for dichotomous moderators are the two values of the moderator.

********************* JOHNSON-NEYMAN TECHNIQUE **************************

Moderator value(s) defining Johnson-Neyman significance region(s):
      Value    % below    % above
     3.1219    71.1340    28.8660

Conditional effect of X on Y at values of the moderator (M)
   bcope_ma     Effect         se          t          p       LLCI       ULCI
    -8.7526   -21.5357     6.2472    -3.4472      .0009   -33.9415    -9.1299
    -7.5526   -20.2438     5.6176    -3.6037      .0005   -31.3993    -9.0884
    -6.3526   -18.9520     5.0320    -3.7663      .0003   -28.9445    -8.9594
    -5.1526   -17.6601     4.5077    -3.9178      .0002   -26.6114    -8.7088
    -3.9526   -16.3682     4.0683    -4.0234      .0001   -24.4471    -8.2893
    -2.7526   -15.0763     3.7440    -4.0268      .0001   -22.5112    -7.6415
    -1.5526   -13.7845     3.5662    -3.8653      .0002   -20.8663    -6.7026
     -.3526   -12.4926     3.5571    -3.5120      .0007   -19.5563    -5.4289
      .8474   -11.2007     3.7178    -3.0127      .0033   -18.5835    -3.8179
     2.0474    -9.9089     4.0280    -2.4600      .0157   -17.9078    -1.9099
     3.1219    -8.7521     4.4073    -1.9858      .0500   -17.5041      .0000
     3.2474    -8.6170     4.4567    -1.9335      .0562   -17.4672      .2333
     4.4474    -7.3251     4.9734    -1.4729      .1442   -17.2012     2.5510
     5.6474    -6.0332     5.5534    -1.0864      .2801   -17.0612     4.9947
     6.8474    -4.7414     6.1790     -.7673      .4448   -17.0117     7.5290
     8.0474    -3.4495     6.8377     -.5045      .6151   -17.0279    10.1289
     9.2474    -2.1576     7.5208     -.2869      .7748   -17.0926    12.7773
    10.4474     -.8657     8.2223     -.1053      .9164   -17.1936    15.4621
    11.6474      .4261     8.9377      .0477      .9621   -17.3225    18.1747
    12.8474     1.7180     9.6641      .1778      .8593   -17.4730    20.9090
    14.0474     3.0099    10.3990      .2894      .7729   -17.6406    23.6603
    15.2474     4.3017    11.1409      .3861      .7003   -17.8219    26.4254

**************************************************************************

Data for visualizing conditional effect of X on Y:
   VisaGrou   bcope_ma       yhat
     -.5464    -5.9635    83.6066
      .4536    -5.9635    65.0736
     -.5464      .0000    75.4850
      .4536      .0000    63.3720
     -.5464     5.9635    67.3635
      .4536     5.9635    61.6705

******************** ANALYSIS NOTES AND WARNINGS *************************

Level of confidence for all confidence intervals in output:
    95.00

NOTE: The following variables were mean centered prior to analysis:
 VisaGrou bcope_ma

NOTE: Some cases were deleted due to missing data.  The number of such cases was:
  6

NOTE: All standard errors for continuous outcome models are based on the HC3 estimator

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