论文标题
GSSMD：一种新的标准化效应尺寸度量，以提高生物应用中的鲁棒性和可解释性
GSSMD: A new standardized effect size measure to improve robustness and interpretability in biological applications
论文作者
论文摘要
在许多生物学应用中，研究的主要目标是量化两组之间的治疗效果的大小。 Cohens'D或严格标准化的平均差异（SSMD）可用于衡量效应大小，但是，它对违反正态性的假设敏感。在这里，我们提出了一个标准化效应大小测量的替代指标，以根据两个样本分布之间的重叠来提高鲁棒性和可解释性。提出的方法是SSMD的非参数广义变体（严格标准化的平均差异）。我们在各种模拟设置中表征了建议的度量，以说明其行为。我们还根据效果大小的估计进行了有限样本特性，并提取了一些准则。作为一个案例研究，我们在RNAi实验中应用了量度，并显示了提出方法的优越性。
In many biological applications, the primary objective of study is to quantify the magnitude of treatment effect between two groups. Cohens'd or strictly standardized mean difference (SSMD) can be used to measure effect size however, it is sensitive to violation of assumption of normality. Here, we propose an alternative metric of standardized effect size measure to improve robustness and interpretability, based on the overlap between two sample distributions. The proposed method is a non-parametric generalized variant of SSMD (Strictly Standardized Mean Difference). We characterized proposed measure in various simulation settings to illustrate its behavior. We also investigated finite sample properties on the estimation of effect size and draw some guidelines. As a case study, we applied our measure for hit selection problem in an RNAi experiment and showed superiority of proposed method.
