用SE绘制3分类& R中的1个连续变量 [英] Point Plot with SE for 3 Categorical & 1 Continuous Variable in R

问题描述

$我试图在包含三个分类变量（mea，tre和sex）的设计中生成一个以单个测量值（len）为单位的单点图。 b $ b

我制作了一个情节，包含所有我想要分割的六个不同的小插图：

但我最好喜欢在可能的情况下将它们全部放在一张图中，优先使用ggplot。

这是我目前的R代码：

  ggplot（mydf，aes（x = factor（mea），y = len），group = sex）+ 
 geom_point（）+ geom_errorbar（limits，width = 0.1）+ facet_wrap（〜tre + sex）
  

以及来自dput的示例数据：

 结构（list（mea = structure c（1L，1L，1L，1L，1L，1L，
 2L，2L，2L，2L，2L，2L），.Label = c（PO_P，Melaniz ），
 tre =结构（c（1L，1L，2L，2L，3L，3L，1L，1L，2L，
 2L，3L，3L），。标签= c （1L，2L，1L，2L，1L，2L，1L，2L，1L，2L）的结构（a，b，c），class =factor ，
 1L，2L），.Label = c（男，女），class =factor），
 N = c（26,26,25,25,27,27 ，14，13，12，11，14，13），len = c（10.6615384615385，
 10.5807692307692,10.292,10.6,10.2851851851852,10.6518518518519，
 11.4785714285714,11.7153846153846,11.7083333333333,11.5，
 11.6214285714286，11.8923076923077），SD = C（0.869057845290829，
 0.779753412698774，0.722218803410712，0.654471797202395，
 0.906686148609193，0.8040141456708，1.0123685642542，0.805032249712347，
 1.13654846981659，0.822192191643779，0.833139171519908，0.739889111580849 
）中， SE = C（0.170436265829955，0.152922225659293，0.144443760682142，
 0.130894359440479，0.174491830656674，0.154732594478434，
 0.270566879755675，0.223275773441538，0.328093282497832，
 0.247900273203854，0.222665809666299，0.205208317689404）
 ci = c（0.351020060264102,0.314949219318153,0.298117269908016,0 
 0.270152680174426,0.35676794.9717481,0.318057403068012，
 0.584524206501098,0.486476119728297,0.722128445903482，
 0.552356230143519,0.481040236068982,0.4447110515336101）），.Names = c（mea ，tre，sex，N，len，sd，se，ci），row.names = c（NA，
 -12L），class =data .frame）
  

解决方案

要区分所有这些分类变量您可以使用颜色，形状，大小，点型等。以下是使用性别和 tre ，

  library（ggplot2）
 limits <-aes（ymax = mydf $ len + mydf $ se ，ymin = mydf $ len-mydf $ se）
 
 ggplot（mydf，aes（x = factor（mea），y = len，color = sex，pch = tre））+ 
 geom_point（position = position_dodge（width = 0.5））+ 
 geom_errorbar（limits，position = position_dodge（width = 0.5））
  

I'm attempting to generate a single plot of points that features the values for a single measurement (len) in a design with three categorical variables (mea, tre, and sex).

I've produced a plot that has all I'm looking for split across six different subplots:

But I'd ideally like to have them all in a single plot if possible, preferentially using ggplot.

Here is my current R code:

ggplot(mydf, aes(x=factor(mea), y=len), group=sex) +
  geom_point() + geom_errorbar(limits, width=0.1) + facet_wrap(~ tre + sex)

And sample data from dput:

structure(list(mea = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 
2L, 2L, 2L, 2L, 2L, 2L), .Label = c("PO_P", "Melaniz"), class = "factor"), 
    tre = structure(c(1L, 1L, 2L, 2L, 3L, 3L, 1L, 1L, 2L, 
    2L, 3L, 3L), .Label = c("a", "b", "c"), class = "factor"), 
    Sex = structure(c(1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 
    1L, 2L), .Label = c("Male", "Female"), class = "factor"), 
    N = c(26, 26, 25, 25, 27, 27, 14, 13, 12, 11, 14, 13), len = c(10.6615384615385, 
    10.5807692307692, 10.292, 10.6, 10.2851851851852, 10.6518518518519, 
    11.4785714285714, 11.7153846153846, 11.7083333333333, 11.5, 
    11.6214285714286, 11.8923076923077), sd = c(0.869057845290829, 
    0.779753412698774, 0.722218803410712, 0.654471797202395, 
    0.906686148609193, 0.8040141456708, 1.0123685642542, 0.805032249712347, 
    1.13654846981659, 0.822192191643779, 0.833139171519908, 0.739889111580849
    ), se = c(0.170436265829955, 0.152922225659293, 0.144443760682142, 
    0.130894359440479, 0.174491830656674, 0.154732594478434, 
    0.270566879755675, 0.223275773441538, 0.328093282497832, 
    0.247900273203854, 0.222665809666299, 0.205208317689404), 
    ci = c(0.351020060264102, 0.314949219318153, 0.298117269908016, 
    0.270152680174426, 0.358673094717481, 0.318057403068012, 
    0.584524206501098, 0.486476119728297, 0.722128445903482, 
    0.552356230143519, 0.481040236068982, 0.447110515336101)), .Names = c("mea", "tre", "sex", "N", "len", "sd", "se", "ci"), row.names = c(NA, 
-12L), class = "data.frame")

解决方案

To differentiate between all those categorical variables you can use color, shape, size, pointtype, etc. Here is an example using color and point type for sex and tre,

library(ggplot2)
limits <- aes(ymax=mydf$len+mydf$se, ymin=mydf$len-mydf$se)

ggplot(mydf, aes(x=factor(mea), y=len, color=sex, pch=tre)) +
  geom_point(position=position_dodge(width=0.5)) +
  geom_errorbar(limits, position=position_dodge(width=0.5))

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