교수님 조절된 매개효과 출력결과 해석에 대해 여쭤봅니다
Run MATRIX procedure:
***************** PROCESS Procedure for SPSS Version 4.2 *****************
Written by Andrew F. Hayes, Ph.D. www.afhayes.com
Documentation available in Hayes (2022). www.guilford.com/p/hayes3
**************************************************************************
Model : 14
Y : interact
X : playfuln
M : creativi
W : parents
Sample
Size: 322
**************************************************************************
OUTCOME VARIABLE:
creativi
Model Summary
R R-sq MSE F df1 df2 p
.338 .114 .178 41.309 1.000 320.000 .000
Model
coeff se t p LLCI ULCI
constant -1.009 .159 -6.356 .000 -1.321 -.697
playfuln .267 .042 6.427 .000 .185 .349
**************************************************************************
OUTCOME VARIABLE:
interact
Model Summary
R R-sq MSE F df1 df2 p
.897 .804 .039 325.348 4.000 317.000 .000
Model
coeff se t p LLCI ULCI
constant 4.219 .080 52.797 .000 4.061 4.376
playfuln .006 .021 .287 .774 -.035 .047
creativi .750 .038 19.547 .000 .674 .825
parents .134 .032 4.204 .000 .071 .197
Int_1 -.092 .044 -2.108 .036 -.179 -.006
Product terms key:
Int_1 : creativi x parents
Test(s) of highest order unconditional interaction(s):
R2-chng F df1 df2 p
M*W .003 4.444 1.000 317.000 .036
----------
Focal predict: creativi (M)
Mod var: parents (W)
Conditional effects of the focal predictor at values of the moderator(s):
parents Effect se t p LLCI ULCI
-.515 .797 .041 19.385 .000 .716 .878
.000 .750 .038 19.547 .000 .674 .825
.515 .702 .048 14.737 .000 .608 .796
****************** DIRECT AND INDIRECT EFFECTS OF X ON Y *****************
Direct effect of X on Y
Effect se t p LLCI ULCI
.006 .021 .287 .774 -.035 .047
Conditional indirect effects of X on Y:
INDIRECT EFFECT:
playfuln -> creativi -> interact
parents Effect BootSE BootLLCI BootULCI
-.515 .213 .042 .137 .301
.000 .200 .040 .128 .284
.515 .187 .039 .118 .270
Index of moderated mediation:
Index BootSE BootLLCI BootULCI
parents -.025 .013 -.053 -.002
*********************** ANALYSIS NOTES AND ERRORS ************************
Level of confidence for all confidence intervals in output:
95.0000
Number of bootstrap samples for percentile bootstrap confidence intervals:
5000
W values in conditional tables are the mean and +/- SD from the mean.
NOTE: The following variables were mean centered prior to analysis:
parents creativi
WARNING: Variables names longer than eight characters can produce incorrect output
when some variables in the data file have the same first eight characters. Shorter
variable names are recommended. By using this output, you are accepting all risk
and consequences of interpreting or reporting results that may be incorrect.
------ END MATRIX -----
교수님 매크로 모델 14번으로 돌렸는데 질문드립니다..
조절된 매개지수 부호가 -로 나오면 조절변수값이 커질수록 매개효과가 작아짐을 의미한다고 알고 있는데요.
그렇다면 조절변수가 큰 집단에서는 매개효과가 작고 상대적으로 조절변인 수준이 낮은 집단에서는 매개효과가 큰 것인데
이것을 효과크기가 아닌 조절변인 수준이 낮은 집단에서는 조절변수가 미치는 영향력이 더 크다고 해석해도 맞는건가요?
단순하게 조절변인 수준이 높을수록 매개효과가 커질거라고 생각했는데 반대로 나와 미궁에 빠지고 있습니다. ㅜㅜ
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이일현 (2025-09-26 14:55:20)
매개효과인 X --> M --> Y 의 효과는 (+) 입니다.
즉, X 가 커지면 M이 커져서 Y 가 커지는 매개효과가 양(+)이라는 것이죠.
그런데 조절된 매개효과가 (-.025) 로 음수입니다.
조절변수의 값이 커질수록 X --> M --> Y 양의 매개효과가 작아지고
반대로
조절변수의 값이 작아질수록 X --> M --> Y 양의 매개효과가 커진다. 입니다.
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