「処置前—処置後」データの解析と平均への回帰

学 岩崎
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引用次数: 4

Abstract

In various research fields, a pretest-posttest experiment is an important and frequently employed method to evaluate treatment effects. In a pretest-posttest experiment, the measurements are made both at baseline and at follow-up in order to eliminate individual variability. There exist several methods that have been proposed to estimate the treatment effect and/or to test that there is no effects at all.In pretest-posttest designs, screening is often made upon the baseline measurements: that is only the individuals who meet some pre-specified requirement are allowed to enter the experiment. In such cases, we have to take into account the effect of the regression to the mean in the analysis to obtain proper conclusions.In this review article, various topics are discussed which are related to pretest-posttest designs and to the regression to the mean as well. We give mathematical results concerning moments of truncated normal distributions, which are useful to understand the underlying theory of the pretest-posttest data. Extensive references are also given.
“处置前—处置后”数据分析和回归平均
在各个研究领域中,前测后测实验是评价治疗效果的重要且常用的方法。在前测后测实验中,测量在基线和随访时进行,以消除个体差异。已经提出了几种方法来估计治疗效果和/或测试根本没有效果。在前测后测设计中,筛选通常是在基线测量上进行的:也就是说,只有满足某些预先规定要求的个体才被允许进入实验。在这种情况下,我们必须在分析中考虑回归均值的影响,以获得适当的结论。在这篇综述文章中,讨论了与前测后测设计和回归均值相关的各种主题。我们给出了截断正态分布矩的数学结果,这有助于理解前测后测数据的基本理论。还提供了广泛的参考文献。
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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