TY - JOUR
T1 - Confidence limits for the indirect effect
T2 - Distribution of the product and resampling methods
AU - Mackinnon, David
AU - Lockwood, Chondra M.
AU - Williams, Jason
N1 - Funding Information:
This research was supported by the National Institute on Drug Abuse grant number 1 R01 DA09757. We acknowledge the contributions of Ghulam Warsi and Jeanne Hoffman to the work described in this article. We thank William Meeker, Leona Aiken, Michael Sobel, Steve West, and Jenn-Yun Tein for comments on an earlier version of this manuscript.
PY - 2004
Y1 - 2004
N2 - The most commonly used method to test an indirect effect is to divide the estimate of the indirect effect by its standard error and compare the resulting z statistic with a critical value from the standard normal distribution. Confidence limits for the indirect effect are also typically based on critical values from the standard normal distribution. This article uses a simulation study to demonstrate that confidence limits are imbalanced because the distribution of the indirect effect is normal only in special cases. Two alternatives for improving the performance of confidence limits for the indirect effect are evaluated: (a) a method based on the distribution of the product of two normal random variables, and (b) resampling methods. In Study 1, confidence limits based on the distribution of the product are more accurate than methods based on an assumed normal distribution but confidence limits are still imbalanced. Study 2 demonstrates that more accurate confidence limits are obtained using resampling methods, with the bias-corrected bootstrap the best method overall.
AB - The most commonly used method to test an indirect effect is to divide the estimate of the indirect effect by its standard error and compare the resulting z statistic with a critical value from the standard normal distribution. Confidence limits for the indirect effect are also typically based on critical values from the standard normal distribution. This article uses a simulation study to demonstrate that confidence limits are imbalanced because the distribution of the indirect effect is normal only in special cases. Two alternatives for improving the performance of confidence limits for the indirect effect are evaluated: (a) a method based on the distribution of the product of two normal random variables, and (b) resampling methods. In Study 1, confidence limits based on the distribution of the product are more accurate than methods based on an assumed normal distribution but confidence limits are still imbalanced. Study 2 demonstrates that more accurate confidence limits are obtained using resampling methods, with the bias-corrected bootstrap the best method overall.
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U2 - 10.1207/s15327906mbr3901_4
DO - 10.1207/s15327906mbr3901_4
M3 - Article
AN - SCOPUS:3042811867
SN - 0027-3171
VL - 39
SP - 99
EP - 128
JO - Multivariate Behavioral Research
JF - Multivariate Behavioral Research
IS - 1
ER -