Statistical properties of four effect-size measures for mediation models.

Milica Miočević, Holly P O'Rourke, David P MacKinnon, Hendricks C Brown
Author Information
  1. Milica Miočević: Department of Psychology, Arizona State University, 950 S. McAllister Ave, Tempe, AZ, 85287, USA. mmiocevi@asu.edu.
  2. Holly P O'Rourke: Department of Psychology, Arizona State University, 950 S. McAllister Ave, Tempe, AZ, 85287, USA.
  3. David P MacKinnon: Department of Psychology, Arizona State University, 950 S. McAllister Ave, Tempe, AZ, 85287, USA.
  4. Hendricks C Brown: Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.

Abstract

This project examined the performance of classical and Bayesian estimators of four effect size measures for the indirect effect in a single-mediator model and a two-mediator model. Compared to the proportion and ratio mediation effect sizes, standardized mediation effect-size measures were relatively unbiased and efficient in the single-mediator model and the two-mediator model. Percentile and bias-corrected bootstrap interval estimates of ab/s , and ab(s )/s in the single-mediator model outperformed interval estimates of the proportion and ratio effect sizes in terms of power, Type I error rate, coverage, imbalance, and interval width. For the two-mediator model, standardized effect-size measures were superior to the proportion and ratio effect-size measures. Furthermore, it was found that Bayesian point and interval summaries of posterior distributions of standardized effect-size measures reduced excessive relative bias for certain parameter combinations. The standardized effect-size measures are the best effect-size measures for quantifying mediated effects.

Keywords

References

  1. Behav Res Methods. 2015 Jun;47(2):424-42 [PMID: 24903690]
  2. Am J Community Psychol. 1993 Jun;21(3):293-31 [PMID: 8311029]
  3. Eval Rev. 1999 Aug;23(4):418-44 [PMID: 10558394]
  4. Multivariate Behav Res. 2013 May 1;48(3):340-369 [PMID: 24039298]
  5. Psychol Methods. 2002 Dec;7(4):422-45 [PMID: 12530702]
  6. J Abnorm Psychol. 2001 Feb;110(1):124-35 [PMID: 11261386]
  7. J Abnorm Psychol. 2000 May;109(2):188-97 [PMID: 10895556]
  8. Health Psychol. 1991;10(3):164-72 [PMID: 1879388]
  9. J Abnorm Psychol. 1999 Feb;108(1):106-19 [PMID: 10066997]
  10. Multivariate Behav Res. 2010 Aug 6;45(4):661-701 [PMID: 26735714]
  11. Behav Res Methods. 2009 May;41(2):486-98 [PMID: 19363189]
  12. J Consult Clin Psychol. 2015 Feb;83(1):157-68 [PMID: 25181028]
  13. Behav Res Methods. 2012 Mar;44(1):213-21 [PMID: 21853410]
  14. Epidemiology. 1991 Sep;2(5):387-92 [PMID: 1742392]
  15. Psychol Methods. 2015 Jun;20(2):193-203 [PMID: 25664380]
  16. Psychol Methods. 2011 Jun;16(2):93-115 [PMID: 21500915]
  17. Multivariate Behav Res. 1988 Jan 1;23(1):69-86 [PMID: 26782258]
  18. Prev Sci. 2001 Mar;2(1):15-28 [PMID: 11519372]
  19. J Appl Psychol. 2005 May;90(3):453-67 [PMID: 15910142]
  20. Soc Sci Med. 1983;17(4):227-34 [PMID: 6844955]
  21. Behav Res Methods. 2009 May;41(2):425-38 [PMID: 19363183]
  22. Multivariate Behav Res. 2004 Oct 1;39(4):653-86 [PMID: 26745462]
  23. Multivariate Behav Res. 2012;47(1):61-87 [PMID: 24049213]
  24. Behav Res Methods. 2007 Nov;39(4):979-84 [PMID: 18183915]
  25. Multivariate Behav Res. 1995 Jan 1;30(1):41 [PMID: 20157641]
  26. Am J Epidemiol. 1986 Feb;123(2):203-8 [PMID: 3946370]
  27. Arch Pediatr Adolesc Med. 1996 Jul;150(7):713-21 [PMID: 8673196]
  28. Psychol Methods. 2009 Dec;14(4):301-22 [PMID: 19968395]
  29. Psychometrika. 2011 Oct;76(4):670-90 [PMID: 27519686]
  30. Int J Methods Psychiatr Res. 2014 Dec;23(4):401-10 [PMID: 24942819]
  31. Prev Sci. 2006 Jun;7(2):179-95 [PMID: 16775760]
  32. J Appl Psychol. 2003 Aug;88(4):750-9 [PMID: 12940413]

Grants

  1. P30 DA027828/NIDA NIH HHS
  2. R01 DA009757/NIDA NIH HHS
  3. R01 MH040859/NIMH NIH HHS
  4. R37 DA009757/NIDA NIH HHS

MeSH Term

Bayes Theorem
Bias
Computer Simulation
Humans
Models, Statistical
Negotiating
Sample Size

Word Cloud

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