The DOI matches its Crossref record; 57 of the 58 references it cites were found in a registry or an index.
Advantages of Monte Carlo Confidence Intervals for Indirect Effects
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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In the citing paper
“we computed 95% confidence intervals of the indirect effect using the Monte Carlo resampling method (Preacher & Selig, 2012).”
From The impact of growth mindset training on entrepreneurial action among necessity entrepreneurs: Evidence from a randomized control trial (2023) · cites this paper as Preacher & Selig, 2012
In the citing paper
“Using Monte Carlo simulation, which is well-suited for testing multi-level mediation [48], we confirmed that there was a significant indirect association between ecological threat and prejudice across nations through cultural tightness, 95% CIs [.003, .03].”
From Ecological and cultural factors underlying the global distribution of prejudice (2019) · cites this paper as [48]
Citations
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Addressing Moderated Mediation Hypotheses: Theory, Methods, and Prescriptions
Preacher, K. J., Rucker, D. D., & Hayes, A. F. (2007) · Multivariate Behavioral Research · doi:10.1080/00273170701341316 · Cited by 9,973
Self-citationA comparison of methods to test mediation and other intervening variable effects
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Cited by
Sorted by citations
An index and test of linear moderated mediation
Hayes, A. F. (2015) · Multivariate Behavioral Research · doi:10.1080/00273171.2014.962683 · Cited by 3,979
Hayes, A. F. (2018) · Communication Monographs · doi:10.1080/03637751.2017.1352100 · Cited by 3,516
Hayes, A. F., & Scharkow, M. (2013) · Psychological Science · doi:10.1177/0956797613480187 · Cited by 2,438
Hayes, A. F., & Rockwood, N. J. (2017) · Behaviour Research and Therapy · doi:10.1016/j.brat.2016.11.001 · Cited by 2,350
Determining power and sample size for simple and complex mediation models
Schoemann, A. M., Boulton, A. J., & Short, S. D. (2017) · Social Psychological and Personality Science · doi:10.1177/1948550617715068 · Cited by 1,837
Metadata
- Authors
- Preacher, K. J., & Selig, J. P.
- Affiliations
- Vanderbilt University (US)
- University of New Mexico (US)
- Corresponding author
- Preacher, Kristopher J.
- 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
- 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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