Advantages of Monte Carlo confidence intervals for indirect effects

Preacher, Kristopher J.; Selig, James P.

doi:10.1080/19312458.2012.679848

Cited by 1,908Advanced Causal Inference TechniquesStatistical Methods and Bayesian InferencePsychometric Methodologies and Testing

Advantages of Monte Carlo confidence intervals for indirect effects

Preacher, Kristopher J., Selig, James P.·2012·Communication Methods and Measures

DOI 10.1080/19312458.2012.679848

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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.

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95% confidence intervals of the indirect effect were computed using Monte Carlo resampling.
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There was a significant indirect association between ecological threat and prejudice across nations through cultural tightness, 95% CIs [.003, .03].
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Authors: Preacher, K. J., & Selig, J. P.
Affiliations: Vanderbilt University (US)
University of New Mexico (US)
Corresponding author: Preacher, Kristopher J.
ORCID: Preacher, Kristopher J.
Selig, James P.
Venue: Communication Methods and Measures
Publisher: Informa UK Limited
Published: 2012-04
Volume: 6
Issue: 2
Pages: 77-98
ISSN: 1931-2458 (ISSN-L)
1931-2466
DOI: 10.1080/19312458.2012.679848
OpenAlex: W2104411852
Cited by: 1,908
References: 58
Citations by year: 2026: 237 · 2025: 199 · 2024: 195 · 2023: 183 · 2022: 202 · 2021: 184 · 2020: 138 · 2019: 142 · 2018: 115 · 2017: 90 · 2016: 76 · 2015: 67 · 2014: 52 · 2013: 25 · 2012: 3
FWCI: 45.24
Type: journal article
Language: en
Open access: closed
Locations: Communication Methods and Measures (publishedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
Keywords: indirect effects, mediation analysis, confidence interval construction, bootstrapping, simulation study, summary data, software implementation

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