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最佳(但常常被遗忘)的做法:在随机试验中,通过对每组相对于基线的变化进行单独分析来检验治疗效果是一种误导性的方法。

Best (but oft forgotten) practices: testing for treatment effects in randomized trials by separate analyses of changes from baseline in each group is a misleading approach.

作者信息

Bland J Martin, Altman Douglas G

机构信息

Department of Health Sciences, University of York, York, United Kingdom; and

Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom.

出版信息

Am J Clin Nutr. 2015 Nov;102(5):991-4. doi: 10.3945/ajcn.115.119768. Epub 2015 Sep 9.

Abstract

Researchers often analyze randomized trials and other comparative studies by separate analysis of changes from baseline in each parallel group. This may be the only analysis presented or it may be in addition to the direct comparison of allocated groups. We illustrate this by reference to 3 recently published nutritional trials. We show why this method of analysis may be highly misleading and may produce type I errors far greater than the 5% that we expect. We recommend direct comparison of means between groups with the use of baseline as a covariate if required.

摘要

研究人员通常通过分别分析每个平行组相对于基线的变化来分析随机试验和其他对比研究。这可能是唯一呈现的分析方法,也可能是在对分配组进行直接比较之外的分析。我们通过引用最近发表的3项营养试验来说明这一点。我们展示了为什么这种分析方法可能极具误导性,并且可能产生远高于我们预期的5%的I型错误。如果需要,我们建议使用基线作为协变量对组间均值进行直接比较。

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