What tests need to be done before bootstrapping to test the mediation effect?

Bootstrapping Pre-tests to test the mediation effect include: regression test for the significant relationship between the independent variable and the dependent variable; potential mediating variable significant correlation with the independent variable and the dependent variable; Sobel/Goodman test for the overall significance of the mediation effect ; Conditional effects test whether the mediating variable affects the relationship between the independent variable and the dependent variable; eliminate alternative explanations and ensure sufficient sample size to improve the test effect.

Bootstrapping Tests that need to be performed before testing the mediating effect

Before performing bootstrapping to test the mediating effect, the following needs to be done Test:

1. Regression test

• Checks the significant relationship between the independent variable and the dependent variable.
• Test whether the potential mediating variable is significantly related to the independent variable and the dependent variable.

2. Sobel test or Goodman test

• Test whether the mediation effect is significant overall.
• These tests provide point estimates of the mediation effect and its significance level.

3. Conditional effect test

• #Test whether the relationship between the independent variable and the dependent variable differs depending on the mediating variable.
• This can help determine the role that the mediating variable plays between the independent variable and the dependent variable.

4. Eliminate alternative explanations

• Consider other potential mechanisms that may explain the relationship between the independent and dependent variables.
• Excluding these explanations will enhance the reliability of the mediation effect.

5. Sample size and statistical power

• Ensure that the sample size is large enough to provide sufficient statistical power to detect the mediation effect.
• If the sample size is insufficient, the bootstrapping test results may be unreliable.

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