Missing data in two-way analysis of variance.
Missing data in two-way analysis of variance.
复制标题
双向方差分析中缺失数据。
DOI：
10.1152/ajpregu.1990.258.2.r291
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发表时间：
1990
期刊：
影响因子：
--
通讯作者：
Glantz,SA
中科院分区：
文献类型：
--
作者：
Slinker,BK;Glantz,SA
我们先前描述了方差计算分析的回归方法，该方法允许在方差Am的双向（或更高）分析中分析不平衡设计和缺失数据的实验。J. Physiol.255（Regulatory Integrative Comp.Physiol.24）：R353-R367，1988。这种方法只能在一系列狭窄的、相对无趣的情况下正确使用。事实上，在我们的例子中，我们将该方法扩展到了预期范围之外，并且错误地计算了F统计量，以检验关于肾脏Na（+）-K（+）-腺苷三磷酸酶研究中大鼠品系和肾单位部位的主要影响的假设。本文提出了正确的方法，它可以推广到大多数情况下可能会遇到的双向，或更高，方差分析使用。
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.