Braitman L E
Office for Research Development, Albert Einstein Medical Center, Philadelphia, Pennsylvania 19141.
J Biopharm Stat. 1993 Sep;3(2):249-56. doi: 10.1080/10543409308835063.
Statistical estimates and significance tests address distinct (but related) questions using the same data. Point estimates and confidence intervals of differences are statistical estimates that address: "How LARGE is the difference in the population of interest?" A significance test addresses the question: "How LIKELY was the difference to have occurred by chance?" Because p-values deal with the existence of a real nonzero difference between treatments but not the size of that treatment difference, they cannot be used to assess clinical (practical) significance. A confidence interval is a range of values used to infer both the size of a difference and the uncertainty of the estimate. Examples illustrate how confidence intervals help us assess both the clinical significance and the statistical significance of an observed difference. The point estimate is the outcome difference actually observed in the study sample; it is also the best single-number estimate of the unknown difference in the sampled population. Point estimates, confidence intervals, and p-values extract complementary information from study data and should all be reported for major results.
统计估计和显著性检验使用相同的数据来解决不同（但相关）的问题。差异的点估计和置信区间是解决以下问题的统计估计：“在感兴趣的总体中差异有多大？” 显著性检验解决的问题是：“该差异偶然发生的可能性有多大？” 由于p值处理的是治疗之间存在实际非零差异的情况，而不是该治疗差异的大小，因此它们不能用于评估临床（实际）意义。置信区间是用于推断差异大小和估计不确定性的一系列值。示例说明了置信区间如何帮助我们评估观察到的差异的临床意义和统计意义。点估计是在研究样本中实际观察到的结果差异；它也是抽样总体中未知差异的最佳单数值估计。点估计、置信区间和p值从研究数据中提取互补信息，对于主要结果都应予以报告。
