Small Sample Mediation Testing: Misplaced Confidence in Bootstrapped Confidence Intervals
Small Sample Mediation Testing: Misplaced Confidence in Bootstrapped Confidence Intervals
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DOI：
10.1037/a0036635
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发表时间：
2015-01-01
影响因子：
9.9
通讯作者：
Sin, Hock-Peng
中科院分区：
文献类型：
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作者：
Koopman, Joel;Howe, Michael;Sin, Hock-Peng
自举是心理学中常用的一种分析工具，用于检验中介模型中间接效应的统计显著性。Bootstrapping的支持者特别主张将其用于20-80个案例的样本。这一主张受到了关注，特别是在《应用心理学杂志》上，因为研究人员越来越多地利用自助法来测试这一范围内的样本。我们讨论的原因是关注这种升级，并在模拟研究中专门集中在这个范围内的样本量，我们不仅证明了自举有足够的统计能力，在大多数情况下，提供一个严格的假设检验，而且自举有一种倾向，表现出膨胀的I型错误率。然后，我们扩展我们的模拟，调查替代的经验reservation方法以及贝叶斯方法，并证明他们表现出可比的统计功率，在小样本的自举没有相关的膨胀I型错误。研究人员在小样本测试中介假设的影响。对于希望在自己的研究中使用这些方法的研究人员，我们在在线补充材料中提供了R语法。
Bootstrapping is an analytical tool commonly used in psychology to test the statistical significance of the indirect effect in mediation models. Bootstrapping proponents have particularly advocated for its use for samples of 20-80 cases. This advocacy has been heeded, especially in the Journal of Applied Psychology, as researchers are increasingly utilizing bootstrapping to test mediation with samples in this range. We discuss reasons to be concerned with this escalation, and in a simulation study focused specifically on this range of sample sizes, we demonstrate not only that bootstrapping has insufficient statistical power to provide a rigorous hypothesis test in most conditions but also that bootstrapping has a tendency to exhibit an inflated Type I error rate. We then extend our simulations to investigate an alternative empirical resampling method as well as a Bayesian approach and demonstrate that they exhibit comparable statistical power to bootstrapping in small samples without the associated inflated Type I error. Implications for researchers testing mediation hypotheses in small samples are presented. For researchers wishing to use these methods in their own research, we have provided R syntax in the online supplemental materials.