Interaction Plot in ggplot2

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情深已故 2020-12-28 16:16

I\'m trying to make interaction plot with ggplot2. My code is below:

library(ggplot2)
p <- qplot(as.factor(dose), len, data=ToothGrowth, geom         


        
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  • 2020-12-28 16:38

    If you think you might need a more general approach, you could try function rxnNorm in package HandyStuff (github.com/bryanhanson/HandyStuff). Disclaimer: I'm the author. Disclaimer #2: the box plot option doesn't quite work right, but all the other options are fine.

    Here's an example using the ToothGrowth data:

    p <- rxnNorm(data = ToothGrowth, res = "len", fac1 = "dose", fac2 = "supp", freckles = TRUE, method = "iqr", fac2cols = c("red", "green"))
    print(p)
    

    rxnNorm Demo

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  • 2020-12-28 16:39

    You can precalculate the values in their own data frame:

    toothInt <- ddply(ToothGrowth,.(dose,supp),summarise, val = mean(len))
    
    ggplot(ToothGrowth, aes(x = factor(dose), y = len, colour = supp)) + 
        geom_boxplot() + 
        geom_point(data = toothInt, aes(y = val)) +
        geom_line(data = toothInt, aes(y = val, group = supp)) + 
        theme_bw()
    

    enter image description here

    Note that using ggplot rather than qplot makes the graph construction a lot clearer for more complex plots like these (IMHO).

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  • 2020-12-28 16:48

    You can compute your summaries by the appropriate groups (supp):

    p <- qplot(as.factor(dose), len, data=ToothGrowth, geom = "boxplot", color = supp) + theme_bw()
    p <- p + labs(x="Dose", y="Response")
    p <- p + stat_summary(fun.y = mean, geom = "point", color = "blue", aes(group=supp))
    p <- p + stat_summary(fun.y = mean, geom = "line", aes(group = supp))
    p <- p  + opts(axis.title.x = theme_text(size = 12, hjust = 0.54, vjust = 0))
    p <- p  + opts(axis.title.y = theme_text(size = 12, angle = 90,  vjust = 0.25))
    print(p)
    

    Or converting to ggplot syntax (and combining into one expression)

    ggplot(ToothGrowth, aes(as.factor(dose), len, colour=supp)) +
      geom_boxplot() +
      stat_summary(aes(group=supp), fun.y = mean, geom="point", colour="blue") +
      stat_summary(aes(group=supp), fun.y = mean, geom="line") +
      scale_x_discrete("Dose") +
      scale_y_continuous("Response") +
      theme_bw() +
      opts(axis.title.x = theme_text(size = 12, hjust = 0.54, vjust = 0),
        axis.title.y = theme_text(size = 12, angle = 90,  vjust = 0.25))
    

    EDIT:

    To make this work with 0.9.3, it effectively becomes Joran's answer.

    library("plyr")
    summ <- ddply(ToothGrowth, .(supp, dose), summarise, len = mean(len))
    
    ggplot(ToothGrowth, aes(as.factor(dose), len, colour=supp)) +
      geom_boxplot() +
      geom_point(data = summ, aes(group=supp), colour="blue", 
                 position = position_dodge(width=0.75)) +
      geom_line(data = summ, aes(group=supp), 
                position = position_dodge(width=0.75)) +
      scale_x_discrete("Dose") +
      scale_y_continuous("Response") +
      theme_bw() +
      theme(axis.title.x = element_text(size = 12, hjust = 0.54, vjust = 0),
            axis.title.y = element_text(size = 12, angle = 90,  vjust = 0.25))
    

    enter image description here

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  • 2020-12-28 16:52

    a much easier way. without ddply. directly with ggplot2.

    ggplot(ToothGrowth, aes(x = factor(dose) , y=len , group = supp, color = supp)) + 
      geom_boxplot() +
      geom_smooth(method = lm, se=F) +
      xlab("dose") +
      ylab("len")
    
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