Comparing Alternative Corrections for Bias in the Bias-Corrected Bootstrap Test of Mediation

Donna Chen, Matthew S. Fritz

Research output: Contribution to journalArticlepeer-review

Abstract

Although the bias-corrected (BC) bootstrap is an often-recommended method for testing mediation due to its higher statistical power relative to other tests, it has also been found to have elevated Type I error rates with small sample sizes. Under limitations for participant recruitment, obtaining a larger sample size is not always feasible. Thus, this study examines whether using alternative corrections for bias in the BC bootstrap test of mediation for small sample sizes can achieve equal levels of statistical power without the associated increase in Type I error. A simulation study was conducted to compare Efron and Tibshirani’s original correction for bias, z0, to six alternative corrections for bias: (a) mean, (b–e) Winsorized mean with 10%, 20%, 30%, and 40% trimming in each tail, and (f) medcouple (robust skewness measure). Most variation in Type I error (given a medium effect size of one regression slope and zero for the other slope) and power (small effect size in both regression slopes) was found with small sample sizes. Recommendations for applied researchers are made based on the results. An empirical example using data from the ATLAS drug prevention intervention study is presented to illustrate these results. Limitations and future directions are discussed.

Original languageEnglish (US)
Pages (from-to)416-427
Number of pages12
JournalEvaluation and the Health Professions
Volume44
Issue number4
DOIs
StatePublished - Dec 2021

Keywords

  • Winsorized means
  • bias-corrected bootstrap
  • corrections for bias
  • indirect effects
  • tests of mediation

ASJC Scopus subject areas

  • Health Policy

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