Advantages of Monte Carlo Confidence Intervals for Indirect Effects
TLDR
This study discusses Monte Carlo confidence intervals for indirect effects, reports the results of a simulation study comparing their performance to that of competing methods, demonstrates the method in applied examples, and discusses several software options for implementation in applied settings.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.read more
Citations
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An Index and Test of Linear Moderated Mediation.
TL;DR: This test can be used for models that integrate moderation and mediation in which the relationship between the indirect effect and the moderator is estimated as linear, including many of the models described by Edwards and Lambert (2007) and Preacher, Rucker, and Hayes (2007), as well as extensions of these models to processes involving multiple mediators operating in parallel or in serial.
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The Relative Trustworthiness of Inferential Tests of the Indirect Effect in Statistical Mediation Analysis Does Method Really Matter
Andrew F. Hayes,Michael Scharkow +1 more
TL;DR: It is found that tests agree much more frequently than they disagree, but disagreements are more common when an indirect effect exists than when it does not and the bias-corrected bootstrap confidence interval is recommended as the most trustworthy test if power is of utmost concern.
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Regression-based statistical mediation and moderation analysis in clinical research: Observations, recommendations, and implementation.
TL;DR: The goal of this paper is to nudge clinical researchers away from historically significant but increasingly old school approaches toward modifications, revisions, and extensions that characterize more modern thinking about the analysis of the mechanisms and contingencies of effects.
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Partial, conditional, and moderated moderated mediation: Quantification, inference, and interpretation
TL;DR: The authors extended this approach to models with more than one mediator and showed that the indirect effect of a mediator depends on a fourth variable, i.e., a second mediator.
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Reliability Estimation in a Multilevel Confirmatory Factor Analysis Framework
TL;DR: It is shown that Monte Carlo confidence intervals and Bayesian credible intervals closely reflect the sampling distribution of reliability estimates under most conditions and that small cluster size can lead to overestimates of reliability at the between level of analysis.
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