Mediation

Purpose:

To assess a third or "black-box" variable in the middle of a casual relationship. It tests a hypothetical causal chain where the independent variable (X or IV) affects a mediator variable (M), which in turn affects the dependent variable (Y or DV).

Context Used:

• Testing a "third variable" after determining a causal relationship between the IV (X) and DV (Y).

Jamovi Walkthrough:

1. Run a linear regression, and continue if significant (See "Regression" tutorial page for more detailed instructions). 

2. Click "Modules" in the upper right-hand corner

3. Click "jamovi library"

4. Search for "medmod" under the "Available" tab and click "Install"

5. Click "medmod"

6. Click "Mediation"

7. Move the DV into the "Dependent Variable" box

8. Move the IV into the "Predictor" box

9. Move the third variable of interest into the "Mediator" box

10. Check "Labels" under "Estimates"

11. Check "Test statistics" under "Estimates"

12. Check "Confidence interval" under "Estimates"

13. Check "Percent mediation" under "Estimates"

14. Check "Path estimates" under "Additional output"

Output Interpretation:

p-value: The probability of detecting a meaningful relationship/difference when there is none. Looking for a small value (p < 0.5).

If p < 0.5, reject the null hypothesis. It IS a significant effect.

If p > 0.5, accept the null hypothesis. It is NOT a significant effect.

% mediation: Indicates how much of the relationship the effect accounts for.

If % is higher for an indirect effect, there is a higher effect of exposure (IV) on the outcome (DV) through the mediator.

If % is higher for a direct effect, there is a higher effect of exposure (IV) on the outcome (DV) absent the mediator.

If % is split between indirect and direct effect, it indicates a partial mediation.

If % is not split between indirect and direct effect, there is a full mediation (Note: this rarely happens in practice)

Types of Effects in Mediation:

Direct Effect (c'): The effect of the IV on the DV, controlling for the mediator.

Indirect Effect (a*b): The effect of the IV on the DV through the mediator.

Total Effect (c): The combined direct and indirect effects of the IV on the DV.

APA Format:

Appropriate data visualization: Path model or Table

Sample table: See below

Sample write-up:

See https://www.starcresto.com/blog/mediation-spss for a sample APA format write-up.

Or, see the image below. (Note: The analysis in the image was completed in SPSS rather than Jamovi, but the values and interpretation remian the same, and the output format is similar enough to follow along).