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Achieving accurate confidence interval estimation for indirect effects
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In this journal article, we demonstrate why normal theory confidence intervals for indirect effects are often less accurate than those obtained from the asymmetric distribution of the product or from bootstrapping.
The distribution of the product has several useful applications. One of these applications is its use to form confidence intervals for the indirect effect as the product of two regression coefficients. The purpose of this article was to investigate how the moments of the distribution of the product explain normal theory mediation confidence interval coverage and imbalance. Values of the critical ratio for each random variable are used to demonstrate how the moments of the distribution of the product change across values of the critical ratio observed in research studies. Results of the simulation study showed that as skewness in absolute value increases, coverage decreases. And as skewness in absolute value and kurtosis increases, imbalance increases. The difference between testing the significance of the indirect effect using the normal theory versus the asymmetric distribution of the product is further illustrated with a real data example. This article is the first study to show the direct link between the distribution of the product and indirect effect confidence intervals and clarifies the results of previous simulation studies by showing why normal theory confidence intervals for indirect effects are often less accurate than those obtained from the asymmetric distribution of the product or from resampling methods. Reference: Kisbu-Sakarya, Y., MacKinnon, D. P., & Miočević, M. (2014). The Distribution of the Product Explains Normal Theory Mediation Confidence Interval Estimation. Multivariate Behavioral Research, 49, 261-268. Link |