Hayes Process Macro - Model 5 - Moderation and Mediation Analyses

Hayes Process Macro - Model 5 - Multiple Mediators and a Moderator

Hayes Process Macro - Lecture Series

The tutorial will guide on Model 5 of the Hayes Process Macro for Moderation and Mediation.

Model 5

  • Example Variables: 1 predictor X, 2 Mediators M, 1 Moderator W, and 1 Outcome Y
  • The variables are continuous.
  • Note: Model 5 allows up to 10 mediators operating in parallel.

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

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 Perceived Organizational Support (POS)
    • Model Number is 5
 
  • 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, W is the Moderator.

Output Interpretation - Model Summary

  1. Model Summary, provides summary of the model with R, R-Sq, F Statistics, and P value for the overall model.
  2. Next, is the coefficients, with impact of Culture on Assurance.
  3. Culture has a significant impact on Assurance (b = 0.5382, t = 11.0324, p < 0.001). This is path a1.
  4. Culture has a significant impact on Perceived Organizational Support (b = 0.7665, t = 17.5325, p < 0.001). This is path a2.

Output Interpretation - For Outcome Organizational Performance (OP)

  • Culture has a significant impact on OP (b = 0.2185, t = 3.7102, p < 0.001). Here this is Direct effect (c’).
  • Assurance was found to have a significant impact on OP (b = 0.2937, t = 6.1559, p < 0.001). This is path b1.
  • Perceived Organizational Support was also found to have a significant impact on OP (b = 0.1916, t = 3.7055, p < 0.001). This is path b2.
  • R-Sq change was also found significant (p = 0.0764/2) (1-tailed)

Next, is the output for OP

 

Johnson-Neyman intervals and simple slopes analysis

  • Johnson-Neyman interval tells you the range of values of the moderator in which the slope of the predictor is significant vs. nonsignificant at a specified alpha level
  • In simple terms Johnson-Neyman identifies regions in the range of the moderator variable where the effect of the focal predictor on the outcome is statistically significant and not significant.

Indirect, Direct, and Total Effect

  • Indirect Effect 1 (a1*b1):

–Culture -> Assurance -> Performance

–a1 (0.5382) * b1 (0.2937) = 0.1581

  • Indirect Effect 2 (a2*b2):

–Culture -> POS -> Performance

–a2 (0.7665) * b2 (0.1916) = 0.1469

  • Direct Effect = 0.2185
  • Is there a Mediation: Yes

–Indirect Effects are Significant.

  • Is it Full or Partial

–Partial, Since both Total and Direct Effects are Significant.

  • Is it Complementary or Competitive
  • a*b*c’ (If Positive: Complimentary)
  • a*b*c’ (If Negative: Competitive)
  • Complimentary. The Sign of Direct and Indirect Effect is same.

Visualizing Effects

  • 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.
  • 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. (I have simply connected the dots, the next section presents the interpretation.

Interpretation of Graph

  • The graph shows a steeper gradient for low and average role ambiguity. The impact of culture on OP is much stronger at low and average role ambiguity. However, at higher role ambiguity, the line tends to straighten, this shows that at higher role ambiguity, the increase in collaborative culture does not lead to significant change in the organizational performance. In conclusion, higher role ambiguity weakens the impact of collaborative culture on organizational performance.

Next,the Conditional effect of X on Y can also help in the interpretation of the graph.

Reporting Moderation Analysis

Moderation Analysis

H1: Role Ambiguity Moderates the Relationship between Collaborative Culture and Organizational Performance such that higher role ambiguity weakens the positive impact of collaborative culture on organizational performance.

To test the hypothesis that the role ambiguity moderates the relationship between collaborative culture and organizational performance, Hayes process macro was utilized.

These interaction/moderating effect (Culture * Role Ambiguity) accounted for a significant (at 10% confidence interval) amount of variance in organizational performance, R2 = .0051, p = .00764. 0.51% change in the organizational performance can be accounted to the interaction term.

To avoid potentially problematic high multicollinearity with the interaction term, the variables were centered and an interaction term between collaborative culture and role ambiguity was created (Aiken & West, 1991).

The results revealed a significantly negative moderating role of role ambiguity on the linkage between collaborative culture and organizational performance (b = -.0570, t = -1.7776, p = 0.0764). This shows that a higher lever of role ambiguity, the impact of collaborative culture on organizational performance is weakened.

Furthermore, the graph shows a steeper gradient for low and average role ambiguity. The impact of culture on OP is much stronger at low and average role ambiguity. However, at higher role ambiguity, the line tends to straighten, this shows that at higher role ambiguity, the increase in collaborative culture does not lead to significant change in the organizational performance. Hence, higher role ambiguity weakens the impact of collaborative culture on organizational performance.

 

Reporting Mediation Analysis

Mediation Analysis

H2: Assurance Mediates the Relationship between Collaborative Culture and Organizational Performance

H3: Perceived Organizational Support (POS) Mediates the Relationship between Collaborative Culture and Organizational Performance

The study assessed the mediating role of assurance and Perceived Organizational Support (POS) on the relationship between collaborative culture and organizational performance. The results revealed a significant indirect effect of of collaborative culture on organizational performance through assurance (b= 0.158, t = 3.856), supporting H2. The study also found a significant indirect effect on the impact of collaborative culture on organizational performance through POS (b= 0.147, t = 3.323), supporting H3. Furthermore, the direct effect of collaborative culture on organizational performance in presence of the mediators was also found significant (b = 0.218, p < 0.001). Hence, both assurance and POS partially mediated the relationship between collaborative culture and organizational performance. Mediation summary is presented in Table 1.

Video Tutorial

Additional Hayes Process Macro Tutorials