Royal College of Surgeons in Ireland, Dublin, Ireland.
Physiotherapy. 2011 Dec;97(4):309-12. doi: 10.1016/j.physio.2011.08.004. Epub 2011 Oct 13.
The calculation of effect size is an important step in measuring the potential real-life significance of the effect of an intervention. In the case of continuous data, Cohen's d is frequently used. This scales the difference between the means of two groups, or the mean difference between pairs of measurements, by dividing by the standard deviation. However, outlying values, especially in small studies, can influence the size of d. This article presents D537, a robust formula for d that is based on rank statistics. The median is used as a measure of difference, while the scaling factor is the range between the 30th and 70th percentiles of the distribution; a range that is equal to one standard deviation when the data are normally distributed. When data are normally distributed, the value of D537 is equal to that of Cohen's d. As D537 is based on the 30th, 50th and 70th percentiles, it is robust to outliers.
效应量的计算是衡量干预效果实际意义的重要步骤。在连续数据的情况下，经常使用 Cohen's d。它通过除以标准差，对两组均值之间的差异或对配对测量值之间的均值差异进行缩放。然而，离群值，特别是在小研究中，会影响 d 的大小。本文提出了 D537，这是一种基于秩统计的稳健 d 公式。中位数用作差异的度量，而缩放因子是分布的第 30 百分位数和第 70 百分位数之间的范围；当数据呈正态分布时，该范围等于一个标准差。当数据呈正态分布时，D537 的值等于 Cohen's d 的值。由于 D537 基于第 30、50 和 70 百分位数，因此对离群值具有稳健性。
