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Communication Methods and Measures· 2012Q1

Advantages of Monte Carlo Confidence Intervals for Indirect Effects

Kristopher J. Preacher, James P. Selig

Short summary

Monte Carlo simulation offers a robust and efficient method for constructing confidence intervals for indirect effects in mediation analysis, outperforming or matching rival methods in various scenarios.

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Key points

  • Monte Carlo simulation is a viable, underutilized method for indirect effect confidence intervals in mediation analysis.
  • Its performance is comparable to other accepted interval construction methods.
  • It can be used with summary data and in situations where bootstrapping or distribution of the product methods are infeasible.
  • The method is less computer-intensive than some alternatives.

AI-generated from the title and abstract; the full text is not read.

Abstract

Monte Carlo simulation is a useful but underutilized method of constructing confidence intervals for indirect effects in mediation analysis. The Monte Carlo confidence interval method has several distinct advantages over rival methods. Its performance is comparable to other widely accepted methods of interval construction, it can be used when only summary data are available, it can be used in situations where rival methods (e.g., bootstrapping and distribution of the product methods) are difficult or impossible, and it is not as computer-intensive as some other methods. In this study we discuss Monte Carlo confidence intervals for indirect effects, report the results of a simulation study comparing their performance to that of competing methods, demonstrate the method in applied examples, and discuss several software options for implementation in applied settings.

The authors' abstract, as published at the source. Communication Methods and Measures, 2012 · DOI ↗

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Field: Statistics and Probability

Statistics and ProbabilityMathematics