R中anova boxplot上的Posthoc标签

Question

如果我有一些数据并进行ANOVA和事后测试，我如何制作一个自动添加事后分类的箱线图，而不是必须在R外编辑图？

例如，以下是一些入门数据：

install.packages("reshape", dependencies=T)
library(reshape)

x <- rnorm(30)
y <- rnorm(30)+1
z <- rnorm(30)+0.5

data.1 <- data.frame(x, y, z)
data.2 <- melt(data.1)

以下是运行简单单向ANOVA和所有未计划的比较事后测试的代码：

linear.model <- lm(value~variable, data=data.2)
anova(linear.model)

# Analysis of Variance Table
# Response: value
#           Df Sum Sq Mean Sq F value   Pr(>F)   
# variable   2 10.942  5.4710  5.8628 0.004087 **
# Residuals 87 81.185  0.9332     

TukeyHSD(aov(linear.model))

# Tukey multiple comparisons of means
# 95% family-wise confidence level
# Fit: aov(formula = linear.model)
# $variable
          # diff        lwr        upr     p adj
# y-x  0.8344105  0.2396705 1.42915051 0.0034468
# z-x  0.2593612 -0.3353788 0.85410126 0.5539050
# z-y -0.5750493 -1.1697893 0.01969078 0.0602975

此时，我想对组“a”中的x，组“b”中的y和组“a，b”中的z进行分类。我可以制作一个箱形图，但你怎么用字母注释呢？

boxplot(value~variable, data=data.2)

Answer 1

如果你不介意使用ggplot2包，这就是我如何制作这个数字：

首先，使用文本标签

为数据框（data.2）添加一列

data.2$posthoc[data.2$variable == "x"] <- "a"
data.2$posthoc[data.2$variable == "y"] <- "b"
data.2$posthoc[data.2$variable == "z"] <- "a,b"

安装并加载ggplot2包：

install.packages("ggplot2", dependencies=T)
library(ggplot2)

要理解图中的代码，我将逐步构建它。首先只绘制三组中每一组的均值：

qplot(data=data.2,
    x = variable,
    y = value,
    stat = "summary",
    fun.y = "mean",
    geom = c("point")
    )

接下来，添加文字标签：

qplot(data=data.2,
    x = variable,
    y = value,
    stat = "summary",
    fun.y = "mean",
    label = posthoc,
    vjust = -12,
    geom = c("point", "text")
    )

最后，添加boxplot geom并将其清理一下：

qplot(data=data.2,
    x = variable,
    y = value,
    stat = "summary",
    fun.y = "mean",
    label = posthoc,
    vjust = -12,
    ylim = c(-1, 3.5),
    geom = c("point", "text"),
    main="ggplot2 ANOVA boxplot"
    ) + 
    geom_boxplot(aes(fill=posthoc)) + 
    theme_bw()

Answer 2

这会更简单

library(reshape)

x <- rnorm(30)
y <- rnorm(30)+1
z <- rnorm(30)+0.5

data.1 <- data.frame(x, y, z)
data.2 <- melt(data.1)
data.2$newgroup = factor(data.2$variable,labels=c("a","b","ab")) # only line added
boxplot(value~newgroup, data=data.2)