Dumas-Mallet Estelle, Button Katherine S, Boraud Thomas, Gonon Francois, Munafò Marcus R
Institute of Neurodegenerative Diseases, CNRS UMR-5293, University of Bordeaux, Bordeaux, France; Centre Emile Durkheim, CNRS UMR-5116, University of Bordeaux, Bordeaux, France.
Department of Psychology , University of Bath , Bath , UK.
R Soc Open Sci. 2017 Feb 1;4(2):160254. doi: 10.1098/rsos.160254. eCollection 2017 Feb.
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.
统计功效较低的研究增加了统计学上显著的发现代表假阳性结果的可能性。我们对研究生物、环境或认知参数与神经、精神和躯体疾病之间关联的研究的荟萃分析进行了综述（不包括治疗研究），以便估计这些领域的平均统计功效。将荟萃分析表明的效应大小作为可能的真实效应大小的最佳估计，并假设宣布具有统计学显著性的阈值为5%，我们发现约50%的研究的统计功效在0 - 10%或11 - 20%范围内，远低于通常认为的80%的最低标准。统计功效较低的研究在生物医学科学中似乎很常见，至少在我们搜索策略所涵盖的特定学科领域是这样。然而，我们也观察到有证据表明这部分取决于研究方法，候选基因研究显示平均功效非常低，而使用认知/行为测量的研究显示平均功效较高。这值得进一步研究。
