A New Transformation of Treated-Control Matched-Pair Differences for Graphical Display

P. Rosenbaum
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Abstract

Abstract A new transformation is proposed for treated-minus-control matched pair differences that leaves the center of their distribution untouched, but symmetrically and smoothly transforms and shortens the tails. In this way, the center of the distribution is interpretable, undistorted and uncompressed, yet outliers are clear and distinct along the periphery. The transformation of pair differences, ,is strictly increasing, continuous, differentiable and odd, , so its action in the extreme upper tail mirrors its action in the extreme lower tail. Moreover, the center of the distribution—typically 90% or 95% of the distribution—is not transformed, with for , yet the nonlinear transformation of the tails is barely perceptible as it begins at , in the sense that , where is the derivative of . The transformation is applied to an observational study of the effect of light daily alcohol consumption on the level of HDL cholesterol. The study has three control groups intended to address specific unmeasured biases; so, several types of pair differences require coordinated depiction focused on unmeasured bias, not outliers. An R package tailTransform implements the method, contains the data, and reproduces aspects of the graphs and data analysis.
一种新的图形显示处理控制匹配对差分变换
摘要提出了一种新的处理减控制匹配对差变换,该变换不影响其分布中心,但对称平滑地变换并缩短了尾部。通过这种方式,分布的中心是可解释的、不扭曲的、不压缩的,而外围的异常值是清晰而明显的。对差的变换是严格递增的、连续的、可微的、奇的,所以它在极端上尾的作用反映了它在极端下尾的作用。此外,分布的中心——通常占分布的90%或95%——没有发生变化,但尾部的非线性变化几乎难以察觉,因为它开始于,从某种意义上说,导数在哪里。这种转化应用于一项观察性研究,研究每日少量饮酒对高密度脂蛋白胆固醇水平的影响。该研究有三个对照组,旨在解决特定的未测量偏差;因此,几种类型的配对差异需要协调描述,重点是不可测量的偏差,而不是异常值。R包tailTransform实现该方法,包含数据,并再现图形和数据分析的各个方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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