Mplus code for the mediation, moderation, and moderated mediation model templates from Andrew Hayes' PROCESS analysis examplesModel 74: 1 or more mediators, in parallel if multiple (example uses 1), IV also moderates the MediatorDV path Example Variables: 1 predictor X, 1 mediator M, 1 outcome Y Preliminary notes: The code below assumes that
Model Diagram:
Statistical Diagram:
Model Equation(s): Y = b0 + b1M + c1'X + c2'MX
Algebra to calculate total, indirect and/or conditional effects by writing model as Y = a + bX: Y = b0 + b1M + c1'X + c2'MX
Y = b0 + b1(a0 + a1X) + c1'X + c2'(a0 + a1X)X
Y = b0 + a0b1 + a1b1X + c1'X + a0c2'X + a1c2'XX
Y = (b0 + a1b1) + (a1b1 + c1' + a0c2' + a1c2'X)X
Conditional Indirect effect of X on Y: a1b1 + a1c2'X = a1*(b1 + c2'X)
Mplus code for the model:
! Predictor variable  X
USEVARIABLES = X M Y XM; DEFINE:
ANALYSIS:
! In model statement name each path using parentheses MODEL:
Y ON X (cdash1); ! direct effect of X on Y
[M] (a0);
! Use model constraint to calculate indirect effect MODEL CONSTRAINT:
LOW_X = #LOWX; ! replace #LOWX in the code with your chosen low value of X
! Calc conditional indirect effects of X on Y via M for low, medium, high values of X IND_LOWX = a1*b1 + a1*cdash2*LOW_X;
! Use loop plot to plot conditional indirect effect of X on Y
PLOT(INDX); LOOP(XVAL,1,5,0.1); INDX = (a1*b1 + a1*cdash2*XVAL)*XVAL; PLOT:
OUTPUT:
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