Mplus code for mediation, moderation, and moderated mediation modelsModel 69 (latent variable version): 1 or more mediators, in parallel if multiple (example uses 1), 2 moderators, both moderating both of the IV-Mediator path and the direct IV-DV path, with all 2-way and 3-way interactions, 1 of which also moderates the Mediator-DV path Example Variables: 1 latent predictor X measured by 4 observed variables X1-X4, 1 latent mediator M measured by 4 observed variables M1-M4, 2 latent moderators W and Z, each measured by sets of 4 observed variables W1-W4 and Z1-Z4 respectively, 1 latent outcome Y measured by 4 observed variables Y1-Y4 Preliminary notes: The code below assumes that
  Model Diagram (factor indicator variables omitted for space/clarity reasons): ![]()   Statistical Diagram (factor indicator variables omitted for space/clarity reasons): ![]()   Model Equation(s):
Y = b0 + b1M + b2MW + c1'X + c2'W + c3'Z + c4'XW + c5'XZ + c6'WZ + c7'XWZ
 
Algebra to calculate indirect and/or conditional effects by writing model as Y = a + bX:
Y = b0 + b1M + b2MW + c1'X + c2'W + c3'Z + c4'XW + c5'XZ + c6'WZ + c7'XWZ
Y = b0 + b1(a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ) + b2(a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ)W + c1'X + c2'W + c3'Z + c4'XW + c5'XZ + c6'WZ + c7'XWZ
Y = b0 + a0b1 + a1b1X + a2b1W + a3b1Z + a4b1XW + a5b1XZ + a6b1WZ + a7b1XWZ + a0b2W + a1b2XW + a2b2WW + a3b2ZW + a4b2XWW + a5b2XZW + a6b2WWZ + a7b2XWWZ + c1'X + c2'W + c3'Z + c4'XW + c5'XZ + c6'WZ + c7'XWZ
Y = (b0 + a0b1 + a2b1W + a3b1Z + a6b1WZ + a0b2W + a2b2WW + a3b2ZW + a6b2WWZ + c2'W + c3'Z + c6'WZ) + (a1b1 + a4b1W + a5b1Z + a7b1WZ + a1b2W + a4b2WW + a5b2ZW + a7b2WWZ + c1' + c4'W + c5'Z + c7'WZ)X
One indirect effect(s) of X on Y, conditional on W, Z:
a1b1 + a4b1W + a5b1Z + a7b1WZ + a1b2W + a4b2WW + a5b2ZW + a7b2WWZ = (a1 + a4W + a5Z + a7WZ)(b1 + b2W)
One direct effect of X on Y, conditional on W, Z:
c1' + c4'W + c5'Z + c7'WZ
 
Mplus code for the model:
! Latent predictor variable X measured by X1-X4
USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4 ANALYSIS:
! In model statement first state measurement model
MODEL:
! Measurement model
 
  W@1;
  Z@1;
! Create latent interactions
! Fit structural model and name parameters
   Y ON X(cdash1);
   M ON X (a1);
! Use model constraint subcommand to test conditional indirect effects
! 2 moderators, 3 values for each, gives 9 combinations
MODEL CONSTRAINT:
    LOW_W = -1;   ! -1 SD below mean value of W
    LOW_Z = -1;   ! -1 SD below mean value of Z
! Calc conditional indirect effects for each combination of moderator values
    ILOW_LOZ = a1*b1 + a4*b1*LOW_W + a5*b1*LOW_Z + a7*b1*LOW_W*LOW_Z +     ILOW_MEZ = a1*b1 + a4*b1*LOW_W + a5*b1*MED_Z + a7*b1*LOW_W*MED_Z +     ILOW_HIZ = a1*b1 + a4*b1*LOW_W + a5*b1*HIGH_Z + a7*b1*LOW_W*HIGH_Z + ! Calc conditional direct effects for each combination of moderator values
    DLOW_LOZ = cdash1 + cdash4*LOW_W + cdash5*LOW_Z + cdash7*LOW_W*LOW_Z;
    DLOW_MEZ = cdash1 + cdash4*LOW_W + cdash5*MED_Z + cdash7*LOW_W*MED_Z;
    DLOW_HIZ = cdash1 + cdash4*LOW_W + cdash5*HIGH_Z + cdash7*LOW_W*HIGH_Z;
! Calc conditional total effects for each combination of moderator values
    TLOW_LOZ = ILOW_LOZ + DLOW_LOZ;
    TLOW_MEZ = ILOW_MEZ + DLOW_MEZ;
    TLOW_HIZ = ILOW_HIZ + DLOW_HIZ;
! Use loop plot to plot conditional indirect effect of X on Y for each combination of low, med, high moderator values
    PLOT(PLOW_LOZ PMEW_LOZ PHIW_LOZ PLOW_MEZ PMEW_MEZ PHIW_MEZ     LOOP(XVAL,-3,3,0.1);
    PLOW_LOZ = ILOW_LOZ*XVAL;     PLOW_MEZ = ILOW_MEZ*XVAL;     PLOW_HIZ = ILOW_HIZ*XVAL; PLOT:
OUTPUT:
 
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