Hayes Process Macro - Model 6 - Serial Mediation Analyses

Hayes Process Macro - Model 6 - Serial Mediation

Hayes Process Macro - Lecture Series

The tutorial will guide on Model 6 of the Hayes Process Macro for Serial Mediation.

Model 6

  • Serial mediation hypothesises a causal chain linking of the mediators.
  • Example Variables: 1 predictor X, 2 Mediators M, and 1 Outcome Y
  • The variables are continuous.
  • Note: Model 6 allows up to 4 mediators operating in serial.

Example

  • We want to examine if the construct of Culture has an indirect effect through Assurance and Perceived Organizational Support on the construct of Organizational Performance. Further the moderating effect of Role Ambiguity is also assessed on the linkage between Culture and Organizational Performance
 
  • Indirect effect of Culture on Performance through Commitment: a1*b1
  • Indirect effect of Culture on Performance through Assurance: a2*b2
  • Indirect effect of Culture on Performance through Commitment and Assurance: a1*d*b2

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 Culture
    • Mediators are Assurance (ASR) and Commitment  (COM)
    • Model Number is 6
 
 
  • Step 3: Select Option Button, and Choose the options as shown in the figure below ()
    • Select Show total effect model (only models 4,6,70,81, 82), this is to generate total effect estimates.
    • For Standardized effect, select Standardized effects (mediation-only models).
    • Press Continue

Output Interpretation - Basic Summary

  • Description of Model along with the different variables where Y is Dependent Variable, X is Independent Variable, M1 and M2 are the Mediating Variables.
 

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, Model summary for each outcome variables is presented.
  • First, the outcome variable is Commitment. Culture has a significant impact on Commitment (b = 0.6041, t = 14.1355, p < 0.001). This is path a1.
  • Culture has a significant impact on Assurance (b = 0.2616, t = 4.6362, p < 0.001). This is path a2.
  • Commitment has a significant impact on Assurance (b = 0.4579, t = 8.0511, p < 0.001). This is path d.