对R中每个因子水平进行方差分析 [英] Perform an ANOVA for each individual level of a factor in R

问题描述

我正在寻找一种简便有效的方法来对因子的每个水平进行独立的ANOVA分析.我认为，我目前所拥有的是多余的，并且使工作空间变得混乱.假设我有以下内容:

I am looking for a short and efficient method to run individual ANOVA analysis on each level of a factor. What I currently have, I think, is redundant and clutters the work space. Let's say I have the following:

Letter Number Question
A      1      1
A      2      1
A      3      1
B      1      1
B      2      1
B      3      1
C      1      1
C      2      1
C      3      1

我可以运行以下代码将数据帧分为子集A，B和C:

I could run the following code to split the data frame into subsets A, B, and C:

> list2env(split(data, data$Letter), globalenv())
> ANOVA.A <- aov(Question~Number, data=A)
> ANOVA.B <- aov(Question~Number, data=B)
> ANOVA.C <- aov(Question~Number, data=C)

尽管这为我提供了所需的结果，但它却使工作空间变得混乱.我的实际数据集要大得多，所以我正在寻找更简单，更优雅的东西.

While this provides me with the required results, it clutters the workspace. My actual data set is far larger, so I am seeking something simpler and more elegant.

推荐答案

使用基本lapply:

lapply(split(df, df$Letter), aov, formula=Question ~ Number)

或者使用dplyr:

library(dplyr)
obj <- df %>% group_by(Letter) %>% do(model = aov(Question~Number, data = .))
obj$model

使用data.table:

library(data.table)
df <- as.data.table(df)
df[, list(Model = list(aov(Question ~ Number))), keyby = Letter]$Model

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