Mplus code for the mediation, moderation, and moderated mediation model templates from Andrew Hayes' PROCESS analysis examplesModel 4d: 1 or more mediators, in parallel if multiple (example uses 1) [BASIC MEDIATION], dichotomous outcome 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): logit(Y) = b0 + b1M + c'X
Algebra to calculate total, indirect and/or conditional effects by writing model as Y = a + bX: logit(Y) = b0 + b1M + c'X
logit(Y) = b0 + b1(a0 + a1X) + c'X
logit(Y) = b0 + a0b1 + a1b1X + c'X
logit(Y) = (b0 + a0b1) + (a1b1 + c')X
Indirect effect of X on Y: a1b1  or, if expressed as an odds ratio, exp(a1b1) Direct effect of X on Y: c'  or, if expressed as an odds ratio, exp(c')
Mplus code for the model:
! Predictor variable  X
USEVARIABLES = X M Y; CATEGORICAL = Y; ANALYSIS:
! In model statement name each path using parentheses MODEL:
Y ON X (cdash); ! direct effect of X on Y M ON X (a1); ! Use model constraint to calculate indirect effect, and odds ratio 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:
Leave the OUTPUT: command unchanged.
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