Gardner M J, Altman D G
Br Med J (Clin Res Ed). 1986 Mar 15;292(6522):746-50. doi: 10.1136/bmj.292.6522.746.
Overemphasis on hypothesis testing--and the use of P values to dichotomise significant or non-significant results--has detracted from more useful approaches to interpreting study results, such as estimation and confidence intervals. In medical studies investigators are usually interested in determining the size of difference of a measured outcome between groups, rather than a simple indication of whether or not it is statistically significant. Confidence intervals present a range of values, on the basis of the sample data, in which the population value for such a difference may lie. Some methods of calculating confidence intervals for means and differences between means are given, with similar information for proportions. The paper also gives suggestions for graphical display. Confidence intervals, if appropriate to the type of study, should be used for major findings in both the main text of a paper and its abstract.
对假设检验的过度强调——以及使用P值将结果分为显著或不显著——已经偏离了更有用的解释研究结果的方法，比如估计和置信区间。在医学研究中，研究者通常感兴趣的是确定不同组间测量结果的差异大小，而不是简单地表明其是否具有统计学显著性。置信区间基于样本数据给出了一系列值，总体差异值可能落在这个范围内。文中给出了一些计算均值和均值差异置信区间的方法，以及比例的类似信息。本文还给出了图形展示的建议。如果适合研究类型，置信区间应用于论文正文及其摘要中的主要发现。
