Mplus code for mediation, moderation, and moderated mediation modelsModel 4b (latent variable version): 2 mediators in parallel [BASIC MEDIATION] Example Variables: 1 latent predictor X measured by 4 observed variables X1X4; 2 latent mediators M1 and M2, each measured by 4 observed variables M1_1M1_4 and M2_1M2_4 respectively, 1 latent outcome Y measured by 4 observed variables Y1Y4 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 + b1M1 + b2M2 + c'X
Algebra to calculate total, indirect and/or conditional effects by writing model as Y = a + bX: Y = b0 + b1M1 + b2M2 + c'X
Y = b0 + b1(a01 + a1X) + b2(a02 + a2X) + c'X
Y = b0 + a01b1 + a1b1X + a02b2 + a2b2X + c'X
Y = (b0 + a01b1 + a02b2) + (a1b1 + a2b2 + c')X
Two indirect effects of X on Y: a1b1, a2b2 One direct effect of X on Y: c'
Mplus code for the model:
! Latent predictor variable X measured by X1X4
USEVARIABLES = X1 X2 X3 X4 M1_1 M1_2 M1_3 M1_4 M2_1 M2_2 M2_3 M2_4
ANALYSIS:
! In model statement first state measurement model
MODEL: ! Measurement model
! Fit structural model and name parameters
Y ON X (cdash); ! direct effect of X on Y M1 ON X (a1);
! Use model constraint to calculate specific indirect paths and total indirect effect MODEL CONSTRAINT:
OUTPUT:
Editing required for testing indirect effect(s) using alternative MODEL INDIRECT: subcommand MODEL INDIRECT: offers an alternative to MODEL CONSTRAINT: for models containing indirect effects, where these are not moderated. To use MODEL INDIRECT: instead, you would edit the code above as follows: First, you can remove the naming of parameters using parentheses in the MODEL: command, i.e. you just need: MODEL:
Second, replace the MODEL CONSTRAINT: subcommand with the following MODEL INDIRECT: subcommand: MODEL INDIRECT:
or, more simply, MODEL INDIRECT:
Leave the OUTPUT: command unchanged.
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