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Point Plot with SE for 3 Categorical & 1 Continuous Variable in R

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: 当前情节

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")

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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