Hayes Process Macro - Model 2 - Moderation Analysis with Continuous Moderators
Hayes Process Macro - Lecture Series
The tutorial will guide on Model 2 of the Hayes Process Macro for Moderation Analysis using 2 Continuous Moderators, and Continuous Independent & Dependent Variables.
Model 2: 2 Moderators M & W
- Example Variables: 1 predictor X, 2 Moderators W & M, 1 outcome Y
- The primary IV (variable X) is continuous.
- The Moderators are Continuous.
Example
- IV: Commitment
- MoDV1: Role Ambiguity
- MoDV2: Role Conflict
- DV: OP
How to Run
- Step 1: Analyze -> Regression -> Process v4.0 by Andrew F. Hayes
- Step 2: Put in the Required Variables. In this case,
- Y Variable (Dependent Variable) is OP
- X Variable (Independent Variable) is Commitment (COM)
- Moderator Variable W: is Role Ambiguity (RA)
- Moderator Variable Z: is Role Conflict (RC)
- Model Number is 2
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- Step 3: Select Option Button, and Choose the options as shown in the figure below ()
- Select Generate code for visualizing interaction, this is to generate graphs for slope analysis
- From Mean center for construction of products groups box, select Only continuous variables that define products. This will mean center the variables the are part of the interaction term. We do mean centering to avoid multi-collinearity between predictor variables and the interaction term.
Output Interpretation - Basic Summary
- Description of Model along with the different variables where Y is Dependent Variable, X is Independent Variable, and W & Z are the Moderating Variable.
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Output Interpretation - Model Summary
- Model Summary, provides summary of the model with R, R-Sq, F Statistics, and P value for the overall model. Next, is the coefficients, with impact of Commitment, Bank, and the interaction effects to assess if there is moderation or not.
- Culture has a significant impact on OP.
- RA and its interaction with Culture (int_1) had a significant impact on OP. This shows that RA moderates the relationship between Culture and OP.
- RC and its interaction with Culture (int_2) had an insignificant impact on OP. This shows that RC doesn’t moderate the relationship between Culture and OP.
Output Interpretation - Inreraction & Conditional Effects
- Test of unconditional interaction, this shows the change in R-Sq due to interaction (X*W), this is significant.
- Test of unconditional interaction, this shows the change in R-Sq due to interaction (X*Z), this is insignificant.
- Next, the Conditional effects of the focal predictor at values of the moderator.
Data Visualization
- Next part of the Hayes Process Macro output is about Data Visualization.
- You will see the following code, to get the graph, copy the code by double clicking on the output.
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- Next, Click File menu, New, and then Syntax.
- Paste the Data Visualization code that you copied. Now, Click the Run Selection button.
- You will have the graph with the main output, at the bottom of the Hayes Process Macro original output.