Bootstrap mediation test z-value
Bootstrap mediation test is a statistical technique used to determine the effect of an independent variable (X) on a dependent variable (M) through a mediating variable (M) Y) role. The z-value is a statistic calculated in this test that measures the statistical significance of the mediation effect.
Calculating Bootstrap z-value
The Bootstrap mediation test z-value is calculated by resampling the data multiple times. In each resampled sample, calculate the path coefficient using standard regression techniques:
- a Path: Direct effect of X on M
- b path: M’s direct effect on Y
- c’ path: X’s indirect effect on Y through M
The mediating effect is equal to c' path. To calculate the z-value, divide the mean value of the c' path by its standard deviation:
<code>z = (c' - 0) / σ_c'</code>
where σ_c' is the standard deviation of the c' path.
z-value explanation
The z-value measures the degree of the mediating effect relative to the uncertainty of its estimate. The larger the absolute value of the z-value, the higher the statistical significance of the mediation effect.
- z > 1.96: The mediation effect is statistically significant at the 0.05 level.
- z > 2.58: The mediation effect is statistically significant at the 0.01 level.
- z The mediation effect is not statistically significant at the 0.05 level.
Purpose
Bootstrap mediation test z-value is used to:
- Test whether the mediation effect exists
- Determine the size and direction of the mediating effect
- Determine the statistical significance of the mediating effect
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