Increasing Statistical Power in Mediation Models Without Increasing Sample Size.
Increasing Statistical Power in Mediation Models Without Increasing Sample Size.
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DOI：
10.1177/0163278713514250
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发表时间：
2015-09
影响因子：
2.9
通讯作者：
MacKinnon DP
中科院分区：
文献类型：
--
作者：
Fritz MS;Cox MG;MacKinnon DP
在卫生研究中，检测治疗效果的统计能力不足是一个问题，在进行调解测试时，这个问题更加复杂。一般来说，增加把握度的首选策略是增加样本量，但在许多情况下，无法招募更多的参与者，因此需要使用其他方法来增加统计把握度。这些其他策略中的许多通常应用于方差分析和多元回归模型，可以应用于具有类似结果的中介模型。然而，额外的预测因子或阻塞变量会增加或减少统计功效，这取决于这些变量是否与中介、结果或两者相关。这两种方法的效果上的权力，调解的测试说明通过使用模拟。使用这些方法的健康研究人员的影响进行了讨论。
Inadequate statistical power to detect treatment effects in health research is a problem that is compounded when testing for mediation. In general, the preferred strategy for increasing power is to increase the sample size, but there are many situations where additional participants cannot be recruited, necessitating the use of other methods to increase statistical power. Many of these other strategies, commonly applied to analysis of variance and multiple regression models, can be applied to mediation models with similar results. Additional predictors or blocking variables will increase or decrease statistical power, however, depending on whether these variables are related to the mediator, the outcome, or both. The effect of these two methods on the power for tests of mediation is illustrated through the use of simulations. Implications for health researchers using these methods are discussed.