Question

简介

执行ANOVA后，我们经常进行一系列成对比较。当组的数量相对较大时，成对比较的数量变得非常大（它是triangular number）。在图表上，通常通过用相同的字母标记它们来表示没有显着差异的组，因此具有产生这些字母的函数是很方便的。

目标

我正在尝试在R中构建一个能够接收输入的函数：

TukeyHSD(aov(y~x))
alpha值

..并且输出：

一个字符串列表，用于指示哪些组显着不同，哪些组不显示。

示例

set.seed(10)
d = data.frame(
    y=c(rnorm(100,10),rnorm(100,10),rnorm(100,8.5),rnorm(100,8)),
    x=rep(c("High","MidHigh", "MidLow","Low"), each=100)
)

z=TukeyHSD(aov(y~x,data=d))
z
  Tukey multiple comparisons of means
    95% family-wise confidence level

Fit: aov(formula = y ~ x, data = d)

$x
                      diff         lwr        upr     p adj
Low-High       -1.66461230 -2.02288676 -1.3063378 0.0000000
MidHigh-High    0.04158636 -0.31668810  0.3998608 0.9906564
MidLow-High    -1.33469921 -1.69297367 -0.9764247 0.0000000
MidHigh-Low     1.70619866  1.34792420  2.0644731 0.0000000
MidLow-Low      0.32991309 -0.02836138  0.6881876 0.0834543
MidLow-MidHigh -1.37628557 -1.73456004 -1.0180111 0.0000000

以下是函数fun将执行的操作

fun(Tukey=z, alpha=0.05)
High MidHigh  MidLow     Low 
"A"     "A"     "B"     "B" 

fun(Tukey=z, alpha=0.1)
High MidHigh  MidLow     Low 
"A"     "A"     "B"     "C"

Answer 1

试用multcompView包。

library(multcompView)
multcompLetters(z$x[,4])
##    Low MidHigh  MidLow    High 
##    "a"     "b"     "a"     "b"

总结成对统计测试列表

1 个答案: