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AI 根据所提供的论文材料归类:处理组回归比较本身未交代因果设计,摘要主要支持通用同时推断方法的归类。

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代码、数据与补充材料

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关注这篇论文的作者
John D. Spurrier

三条及以上回归直线所有对比的精确置信界

研究问题
比较三个及以上处理组的简单线性回归函数时,如何为所有对比构造精确同时置信界,并减轻 Scheffé 方法的保守性?
方法与思路
作者在独立同分布正态误差、各组设计矩阵相同的设定下,使用并交方法,并通过 F 分布函数的线性组合计算枢轴量分布。
材料陈述的贡献
摘要称方法提供精确同时置信界;三个和六个处理组时,Scheffé 置信界分别约宽百分之五和百分之十三。
阅读关注点
应核对所覆盖对比与协变量取值的范围、精确性的完整条件,以及摘要所报置信界宽度差异对应的比较设定。
阅读边界
仅据 OpenAlex 索引摘要,稿件版本未注明;不等设计矩阵或非正态误差下的有效性未说明,宽度差异不能视为普遍比例。

原文摘要

It is desired to compare κ ≥ 3 treatments. Under the assumption of iid normal errors, it is well known that the Scheffé method produces exact simultaneous confidence bounds for all contrasts of the treatment means. Furthermore, it is known that the Scheffé method is conservative when one desires confidence bounds for a specific subset of contrasts of means. Exact methods, such as those due to Tukey and Dunnett, yield tighter bounds than the Scheffé method for specific subsets of contrasts of means. In this article, multiple comparisons of the κ treatments are done not in terms of their means, but rather in terms of a parametric function. The parametric function of interest is the simple linear regression model, E(Y|x). It is desired to find simultaneous confidence bounds for all contrasts of the κ simple linear regression models. Although the Scheffé method can be used to find such bounds, this is extremely conservative. The union-intersection method is used to develop simultaneous confidence bounds for these contrasts under the assumption of equal design matrices for each treatment. The method is based on a pivotal quantity whose distribution function is a linear combination of F distribution functions. Thus probability points can be computed using standard computing packages. The Scheffé bounds are about 5% wider than the exact bounds for κ = 3 and about 13% wider for κ = 6.

笔记与分组