How to read the bootstrap mediation effect test results in stata

Interpretation steps of Bootstrap mediation effect test in Stata: Check the sign of the coefficient: determine the positive or negative direction of the mediation effect. Test p value: less than 0.05 indicates that the mediating effect is significant. Check the confidence interval: not containing zero indicates that the mediation effect is significant. Comparing the median p-value: less than 0.05 further supports the significance of the mediation effect.

Interpretation of Bootstrap mediation effect test results in Stata

Bootstrap mediation effect test is a statistical method. Used to evaluate the role of a mediating variable in the relationship between two variables. In Stata, you can use themedtestcommand to perform Bootstrap mediation effect testing.

Interpretation of test results

The test results will contain the following information:

• Coefficient:The size of the mediating effect, That is, the effect of the mediating variable on the dependent variable.
• Standard error:The standard deviation of the estimate of the coefficient.
• t value:The significance test statistic of the coefficient.
• p value:The probability that the coefficient is zero.
• Confidence interval:The estimated range of the coefficient.
• Bias corrected confidence interval:The estimate range is narrow after bias correction.
• Median of p-value:The median of the sampling distribution of the significance of the Bootstrap mediation effect.

Interpretation steps

1. #Check the sign of the coefficient:The sign of the coefficient will indicate whether the mediation effect is positive or negative .
2. Test p value:A p value less than 0.05 indicates that the mediation effect is statistically significant.
3. Check the confidence interval:If the confidence interval does not contain zero, it indicates that the mediation effect is significant.
4. Compare the median p-values:The median p-value is less than 0.05, further supporting the significance of the mediation effect.

Notes

• Bootstrap mediation effect test is only a statistical test and does not provide evidence of causality.
• Test results are sensitive to sample size and data distribution.
• The results should be interpreted in conjunction with other methods (such as the Baron-Hallem test of partial mediation effects).

Example interpretation

medtest y x m, vce(bootstrap, reps(1000))

Output:

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