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Low statistical power in biomedical science: a review of three human research domains

机译:生物医学科学中的统计能力低:三个人类研究领域的回顾

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Studies with low statistical power increase the likelihood that a statistically significant finding represents a false positive result. We conducted a review of meta-analyses of studies investigating the association of biological, environmental or cognitive parameters with neurological, psychiatric and somatic diseases, excluding treatment studies, in order to estimate the average statistical power across these domains. Taking the effect size indicated by a meta-analysis as the best estimate of the likely true effect size, and assuming a threshold for declaring statistical significance of 5%, we found that approximately 50% of studies have statistical power in the 0–10% or 11–20% range, well below the minimum of 80% that is often considered conventional. Studies with low statistical power appear to be common in the biomedical sciences, at least in the specific subject areas captured by our search strategy. However, we also observe evidence that this depends in part on research methodology, with candidate gene studies showing very low average power and studies using cognitive/behavioural measures showing high average power. This warrants further investigation.
机译:具有低统计功效的研究会增加具有统计学意义的发现代表假阳性结果的可能性。我们对研究的荟萃分析进行了综述,以调查生物学,环境或认知参数与神经,精神和躯体疾病之间的联系,但不包括治疗研究,以评估这些领域的平均统计能力。以荟萃分析指示的效应大小作为可能的真实效应大小的最佳估计,并假设声明统计学显着性的阈值为5%,我们发现大约50%的研究在0–10%的范围内具有统计学功效或11–20%的范围,远低于通常认为的80%的最小值。具有较低统计能力的研究似乎在生物医学领域很常见,至少在我们的搜索策略所捕获的特定主题领域中是如此。但是,我们也观察到证据,这部分取决于研究方法,候选基因研究显示出极低的平均功效,而使用认知/行为学方法的研究显示出较高的平均功效。这值得进一步调查。

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