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双向方差分析中的缺失数据。

Missing data in two-way analysis of variance.

作者信息

Slinker B K, Glantz S A

机构信息

Department of Medicine, University of Vermont, Burlington 05405.

出版信息

Am J Physiol. 1990 Feb;258(2 Pt 2):R291-7. doi: 10.1152/ajpregu.1990.258.2.R291.

Abstract

We previously described a regression approach to analysis of variance computations that permitted analysis of unbalanced designs and experiments with missing data in two-way (or higher) analyses of variance Am. J. Physiol. 255 (Regulatory Integrative Comp. Physiol. 24): R353-R367, 1988. That approach can only be used correctly under a set of narrow, and relatively uninteresting, circumstances. In fact, in the example we worked, we extended that approach beyond its intended scope and incorrectly computed F statistics for testing hypotheses about the main effects of strain of rat and nephron site in a study of renal Na(+)-K(+)-adenosinetriphosphatase. This paper presents the correct approach, which can be generalized to most situations likely to be encountered when two-way, or higher, analyses of variance are used.

摘要

我们之前描述了一种用于方差分析计算的回归方法,该方法允许在双向(或更高阶)方差分析中对不平衡设计和存在缺失数据的实验进行分析(《美国生理学杂志》255卷(调节整合与比较生理学24):R353 - R367,1988年)。该方法仅能在一组狭窄且相对无趣的情况下正确使用。实际上,在我们所做的示例中,我们将该方法扩展到了其预期范围之外,并在一项关于肾钠钾三磷酸腺苷酶的研究中,错误地计算了用于检验大鼠品系和肾单位部位主效应假设的F统计量。本文介绍了正确的方法,该方法可推广到使用双向或更高阶方差分析时可能遇到的大多数情况。

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