评论格里菲斯和希尔(2022)的《关于线性模型中假设的f检验的力量》

D. Harville
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引用次数: 0

摘要

本文建立并说明了用三种F检验t1、t2和t3识别的非中心性参数之间的一些关系,这些关系适用于N × 1随机向量y(平均向量X β和方差协方差矩阵σ 2 I)中元素的实现值构成的数据。在接下来的内容中,将展示这些关系可以以一种相对简单的方式建立,这种方式仅使用现成的结果,提供对潜在基本原理的见解,并提供一些潜在有用的扩展。这三个F -检验可以看作是关于j1 × 1向量τ 1 = r1 β和j2 × 1向量τ 2 = r2 β,它们是由β元素的J = j1 + j2线性无关的可估计线性组合形成的:1 J×1常数向量r 1和J 2×1常数向量r 2, T 1是一个测试的零假设τ= rτ=(τ(cid: 2) 1,τ(cid: 2) 2) (cid: 2)和r = (r (cid: 2) 1, r (cid: 2) 2) (cid: 2), T 2是一个测试的零假设τ1 = r(当β无限制)和T 3是一个测试的零假设τ1 = r 1β受限制时τ2 = r 2。由t1、t2和t3确定的非中心性参数为
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comment on “On the Power of the F-test for Hypotheses in a Linear Model,” by Griffiths and Hill (2022)
The authors establish and illustrate some relationships among the noncentrality parameters identified with three F tests T 1 , T 2 , and T 3 applicable to a setting where the data consist of the realized values of the elements of an N × 1 random vector y that is distributed as N ( X β , σ 2 I ) (MVN with mean vector X β and variance-covariance matrix σ 2 I ). In what follows, it is shown that these relationships can be established in a relatively simple way that uses only readily available results, that provides insights into the underlying rationale, and that lends itself to some potentially useful extensions. The three F -tests can be regarded as pertaining to a J 1 × 1 vector τ 1 = R 1 β and a J 2 × 1 vector τ 2 = R 2 β formed from J = J 1 + J 2 linearly independent estimable linear combinations of the elements of β : for a J 1 × 1 vector of constants r 1 and a J 2 × 1 vector of constants r 2 , T 1 is a test of the null hypothesis τ = r where τ = ( τ (cid:2) 1 , τ (cid:2) 2 ) (cid:2) and r = ( r (cid:2) 1 , r (cid:2) 2 ) (cid:2) , T 2 is a test of the null hypothesis τ 1 = r 1 (when β is unrestricted), and T 3 is a test of the null hypothesis τ 1 = r 1 when β is subject to the restriction τ 2 = r 2 . The noncentrality parameters identified with T 1 , T 2 , and T 3 are
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