SE的点图为3分类＆amp; 1 R中的连续变量

Question

我正在尝试生成一个点图，其中包含具有三个分类变量（mea，tre和sex）的设计中单个测量值（len）的值。

我已经制作了一个情节，我正在寻找分为六个不同的子图：

但是如果可能的话，我最好将它们全部放在一个图中，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)

来自dput的示例数据：

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")

Answer 1

要区分所有这些分类变量，您可以使用颜色，形状，大小，点类型等。以下是使用sex和tre的颜色和点类型的示例，

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))