绘制多重比较？ [英] Plotting of multiple comparisons?

问题描述

当希望比较（测试）多个组（例如，当做anova时），人们面临多个比较的问题。如果我们希望绘制比较，同样适用。

我的问题是，因此，什么工具（R）你知道允许反映多个比较？

目前，我只知道两个（虽然我相信还有更多）：

1. TukeyHSD（）与plot（）组合


2. 箱线图选择凹口的方式

$

http://www.r-bloggers.com/multiple-comparisons-for-glmms-using-glmer-glht/rel =nofollow> http://www.r-bloggers.com/multiple-comparisons-for -glmms-using-glmer-glht /

有一篇关于统计分析R-Project手册（网站）的同步推理的文章...

http://cran.r-project.org/web/packages/HSAUR2/vignettes/Ch_simultaneous_inference.pdf

plotmeans（）从gplot包。这包括置信区间。

然后，程序包psych有一个error.bars.by（）函数。

有些使用密度图表进行可视化。

 ＃比较具有
＃4,6或8气缸的汽车的MPG分配
库（sm）
附加（mtcars）
 
＃创建价值标签
 cyl.f < -  factor（cyl，levels = c（4,6,8），
 labels = c（4气缸，6气缸，8气缸 ）
 
＃plot densitys 
 sm.density.compare（mpg，cyl，xlab =Miles Per Gallon）
 title（main =MPG Distribution by Car Cylinders ）
 
＃通过鼠标点击添加图例
 colfill< -c（2：（2 + length（levels（cyl.f））））
 legend（locator ，levels（cyl.f），fill = colfill）
  

When one wishes to compare (test) multiple groups (as is the case, for example, when doing anova), one is confronted with the issue of multiple comparisons. The same applys if we wish to plot the comparisons.

My question is thus, what tools (in R) do you know of that allow plotting that reflects multiple comparisons?

Currently, I know of only two (although I am sure there are more):

1. TukeyHSD( ) combined with plot( )
2. The way boxplot chooses the "notches"

解决方案

There are some methods around for multiple comparisons in GLMs

http://www.r-bloggers.com/multiple-comparisons-for-glmms-using-glmer-glht/

There is an article about simultaneous inference from the R-Project Handbook of Statistical Analyses (website) ...

http://cran.r-project.org/web/packages/HSAUR2/vignettes/Ch_simultaneous_inference.pdf

plotmeans() from the gplot package. That includes confidence intervals.

Then there is a error.bars.by() function of the package "psych". Plots the means and SDs groupwise from a dataframe.

Some use density plots for visualization.

# Compare MPG distributions for cars with 
# 4,6, or 8 cylinders
library(sm)
attach(mtcars)

# create value labels 
cyl.f <- factor(cyl, levels= c(4,6,8),
  labels = c("4 cylinder", "6 cylinder", "8 cylinder")) 

# plot densities 
sm.density.compare(mpg, cyl, xlab="Miles Per Gallon")
title(main="MPG Distribution by Car Cylinders")

# add legend via mouse click
colfill<-c(2:(2+length(levels(cyl.f)))) 
legend(locator(1), levels(cyl.f), fill=colfill)

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