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Small Sample Mediation Testing: Misplaced Confidence in Bootstrapped Confidence Intervals

机译:小样本中介测试:自举置信区间中的置信度错位

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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.
机译:自举是心理学中常用的一种分析工具,用于测试中介模型中间接影响的统计显着性。自举支持者特别提倡将其用于20-80个案例的样本。随着研究人员越来越多地利用自举法来测试该范围内的样品的介导作用,尤其是在《应用心理学杂志》上,这种提倡得到了关注。我们讨论了与这种升级有关的原因,并且在专门针对该样本量范围的模拟研究中,我们不仅证明了自举法在大多数情况下不足以提供严格的假设检验的统计能力,而且还证明了自举法有一种趋势表现出虚高的I型错误率。然后,我们扩展仿真以研究替代的经验重采样方法以及贝叶斯方法,并证明它们表现出与小样本自举相当的统计能力,而没有相关的虚假I型误差。提出了对研究人员在小样本中测试调解假设的启示。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。

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