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This summary is machine-generated.

This study evaluated statistical methods for analyzing indirect effects in single-group and multi-group analyses. Bootstrap confidence intervals and multi-group methods were robust to violated assumptions, unlike some single-group approaches.

Keywords:
group difference in mediationmoderated indirect effectmoderated mediationmulti-group analysissimple indirect effect

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Area of Science:

  • Psychometrics
  • Statistical Methods
  • Behavioral Research

Background:

  • Accurate statistical analysis is crucial for understanding group differences in indirect effects.
  • Existing methods for indirect effect analysis have limitations, particularly under violated assumptions.

Purpose of the Study:

  • To evaluate the performance of statistical methods for testing group differences in indirect effects.
  • To investigate the impact of violated equal variance assumptions on single-group analysis methods.
  • To compare the robustness of single-group and multi-group approaches.

Main Methods:

  • Comparison of statistical methods for indirect effect analysis.
  • Simulation studies to assess performance under violated assumptions.
  • Evaluation of single-group and multi-group analysis frameworks.

Main Results:

  • The assumption of equal variance critically impacted specific single-group methods (product term, Wald test).
  • Bootstrap confidence intervals in single-group analysis remained unaffected by violated assumptions.
  • All methods within the multi-group analysis approach demonstrated robustness to assumption violations.

Conclusions:

  • Multi-group analysis and bootstrap confidence intervals offer reliable approaches for indirect effect testing, even with violated assumptions.
  • Researchers should exercise caution when using certain single-group methods under unequal variances.
  • Recommendations are provided for selecting appropriate statistical methods based on study design and assumptions.