ANALYSIS OF STATISTICAL TESTS TO COMPARE VISUAL ANALOG SCALE MEASUREMENTS AMONG GROUPS
ANALYSIS OF STATISTICAL TESTS TO COMPARE VISUAL ANALOG SCALE MEASUREMENTS AMONG GROUPS
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DOI：
10.1097/00000542-199504000-00012
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发表时间：
1995-04-01
期刊：
影响因子：
8.8
通讯作者：
CHESTNUT, DH
中科院分区：
文献类型：
--
作者：
DEXTER, F;CHESTNUT, DH
背景：麻醉师进行的一种常见类型的研究确定了一组患者报告的对疼痛的干预效果。本研究的目的是评估t检验、方差分析(ANOVA)、Mann-Whitney和Kruskal-Wallis检验在两组或三组患者之间比较视觉模拟评分(VAS)的有效性。这些结果可能在用输精管测量疼痛的研究设计中特别有帮助。方法：从480名接受催产素(149例)、纳布芬(159例)或硬膜外布比卡因(172例)的临产妇女每人获得一次VAS测量。然后从这些数据中提取了多个模拟样本。这些模拟样本被用于临床试验的计算机模拟，比较不同组之间的VAS测量。在使用反正弦变换前后进行t和ANOVA检验，以使数据更接近正态分布。结果：VAS测量值的统计分布为非正态分布(P<；10(-7))。Arcsin变换使分布更接近正态分布。然而，没有错误的统计检验表明，在没有差异的情况下，组间存在差异的情况下，比预期的比率更高。与其他测试相比，Tor ANOVA测试在检测组间差异方面具有更大的统计能力。由于反正弦变换既减小了均值之间的差异，又在较小程度上减小了方差，因此降低了检测组间差异的能力。结论：t和ANOVA，没有伴随的反正弦变换，是发现组间VAS测量差异的良好测试。
Background: A common type of study performed by anesthesiologists determines the effect of an intervention on pain reported by groups of patients. The goal of this study was to evaluate the effectiveness of t, analysis of variance (ANOVA), Mann-Whitney, and Kruskal-Wallis tests to compare visual analog scale (VAS) measurements between two or among three groups of patients. These results may be particularly helpful during the design of studies that measure pain with a VAS.Methods: One VAS measurement was obtained from each of 480 nulliparous women in labor who were receiving oxytocin (149), nalbuphine (159), or epidural bupivacaine (172). Multiple simulated samples were then drawn from these data. These simulated samples were used in computer simulations of clinical trials comparing VAS measurements among groups. t and ANOVA tests were performed before and after an arcsin transformation was used, to make the data closer to a normal distribution. VAS measurements were also compared after they were divided into five ranked categories.Results: The statistical distributions of VAS measurements were not normal (P < 10(-7)). Arcsin transformation made the distributions closer to normal distributions. Nevertheless, no statistical test incorrectly suggested that a difference existed among groups, when there was no difference, more often than the expected rate. tor ANOVA tests had a slightly greater statistical power than the other tests to detect differences among groups. Because arcsin transformation both decreased differences among means and reduced the variance to a lesser extent, it decreased power to detect differences among groups. Statistical power to detect differences among groups was not less for a five-category VAS than for a continuous VAS.Conclusions: We conclude that t and ANOVA, without an accompanying arcsin transformation, are good tests to find differences in VAS measurements among groups.