Tello Richard, Crewson Philip E
Department of Radiology, Boston University School of Medicine, 88 E Newton St, Atrium 2, Boston, MA 02118, USA.
Radiology. 2003 Apr;227(1):1-4. doi: 10.1148/radiol.2271020085. Epub 2003 Feb 28.
Whenever means are reported in the literature, they are likely accompanied by tests to determine statistical significance. The t test is a common method for statistical evaluation of the difference between two sample means. It provides information on whether the means from two samples are likely to be different in the two populations from which the data originated. Similarly, paired t tests are common when comparing means from the same set of patients before and after an intervention. Analysis of variance techniques are used when a comparison involves more than two means. Each method serves a particular purpose, has its own computational formula, and uses a different sampling distribution to determine statistical significance. In this article, the authors discuss the basis behind analysis of continuous data with use of paired and unpaired t tests, the Bonferroni correction, and multivariate analysis of variance for readers of the radiology literature.
每当文献中报告均值时,它们很可能会伴有用于确定统计学显著性的检验。t检验是用于对两个样本均值差异进行统计学评估的常用方法。它提供了有关来自两个样本的均值在数据所源自的两个人群中是否可能存在差异的信息。同样,在比较同一组患者在干预前后的均值时,配对t检验很常见。当比较涉及两个以上均值时,会使用方差分析技术。每种方法都有特定用途,有自己的计算公式,并使用不同的抽样分布来确定统计学显著性。在本文中,作者为放射学文献的读者讨论了使用配对和非配对t检验、Bonferroni校正以及多变量方差分析来分析连续数据的背后依据。