方差分析(ANOVA)。

D. Quicke, B. A. Butcher, R. K. Welton
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引用次数: 0

摘要

当响应变量为数值(实数),解释变量均为分类变量时,方差分析用于分析样本中群体均值之间的差异。每个解释变量可能有两个或两个以上的因素水平,但如果只有一个解释变量,它只有两个因素水平,应该使用学生t检验,结果将是相同的。基本上,方差分析拟合一个或多个分类解释变量的截距和斜率。方差分析通常使用线性模型函数lm或更具体的函数aov来执行,但有一个特殊的函数是单向的。当只有一个解释变量时进行检验。对于单向方差分析,非参数等效(如果方差假设不满足)是kruskal.test。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of variance (ANOVA).
Abstract Analysis of variance is used to analyze the differences between group means in a sample, when the response variable is numeric (real numbers) and the explanatory variable(s) are all categorical. Each explanatory variable may have two or more factor levels, but if there is only one explanatory variable and it has only two factor levels, one should use Student's t-test and the result will be identical. Basically an ANOVA fits an intercept and slopes for one or more of the categorical explanatory variables. ANOVA is usually performed using the linear model function lm, or the more specific function aov, but there is a special function oneway.test when there is only a single explanatory variable. For a one-way ANOVA the non-parametric equivalent (if variance assumptions are not met) is the kruskal.test.
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