plot TOTAL errorbar for multiple lines in ggplot r

Question

I would like to plot the data by subject but adding the errorbar of the total mean and se. I mean, not an error bar for each subject. I've tried geom_errorbar and stat_summary but still failed to get my ideal plot (see the figure I drew).

and here is the code I used to draw this figure (the errorbars are added by hand).

ggplot(ASD, aes(x=period, y=meanF0, group=subject, color=group)) + 
      geom_line(aes(color=group, size=group)) +
      scale_size_manual(values=c(.6, .6, .6, .6)) +
      theme_light()+
      xlab("Period")+
      ylab("F0 (Hz)")+
      ggtitle("Mean F0 Adjustment (ASD Group)") +
      geom_point()+
      scale_color_manual(values=c("red")) +
      theme(plot.title = element_text(size=14.5, face="bold", hjust = 0.5,  family = "serif"), 
            axis.title.y= element_text(size=12, face = "bold", family = "serif"),
            axis.title.x= element_text(size=12, face = "bold", family = "serif"),
            axis.text.x = element_text(size=11, face="bold", family = "serif"),
            axis.text.y = element_text(size=11, face="bold", family = "serif"))+
      theme(legend.position = "none")+
      geom_hline(yintercept=112.8, linetype="dashed", 
                 color = "dark grey", size=.7)

Anyone could help? Thank you very much!!!

It looks like you're fairly new to SO; welcome to the community! If you want great answers quickly, it's best to make your question reproducible. This includes sample data like the output from dput(head(dataObject))) and any libraries you are using (although in this case, it seems pretty likely that it's just ggplot2). Check it out: making R reproducible questions. — Kat
– Kat, Commented Feb 25, 2022 at 5:14

Kat · Accepted Answer · 2022-02-25 06:59:06Z

Use annotate to add the error bars. I don't have your data, so I created my own. You're going to need the confidence interval and the average for each group. My average-by-group values and confidence interval-by-group are stored in df4$meanV and df4$ci. You can replace these with your variable names. In annotate, you'll include the data frame in the call like you would in base R plots. Like base R, you can just use raw values, as well. Multiple values can be joined with c(). As in y = c(12, 10). If you have any questions, just let me know.

ggplot(df2, aes(x = condition, y = value, 
                color = subject, group = subject)) +
  geom_line() + geom_point() + 
  annotate("errorbar",
           x = df4$condition
           ymin = df4$meanV - df4$ci,
           ymax = df4$meanV + df4$ci,
           width = .2) +
  annotate("point",
          x = df4$condition,
          y = df4$meanV) + 
  ylim(min(df2$value), max(df2$value))

Denis Cousineau · Accepted Answer · 2024-11-06 01:28:17Z

Using the library superb, you get a function which computes the means and confidence intervals. You can, using various layouts, display additional information. One such layout displays the individvidual lines with

library(superb)

superb( cbind(value.posttest, value.pretest) ~ ., ASD,
  WSFactors = ("condition(2)"),
  plotStyle = "pointindividualline"
)

You also have access to other layouts. One is called corset-plot. It shows individual lines, but also a smooth density on the sides. Try

superb( cbind(value.posttest, value.pretest) ~ ., ASD,
  WSFactors = ("condition(2)"),
  plotStyle = "corset",
  violinParams = list(fill = "green", alpha = .2) # optional: some color
) + theme_bw() # optional : alternative theme

You get:

Note that I am the maintainer of superb.

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