ggplot2 – issue with overlay of lines and errorbars - r

Question

On the same ggplot figure, I am trying to have the points (from geom_point), the lines (from geom_line) and the errorbars (from geom_errorbar) on the same "plane" (i.e. not overlapping), this for each factor.
As you can see the "layering" of the errorbars is not following the "layering" of the lines (not mentionning the points).
Here is a reproducible example:
# reproducible example
# package
library(dplyr)
library(ggplot2)
# generate the data
set.seed(244)
d1 <- data.frame(time_serie = as.factor(rep(rep(1:3, each = 6), 3)),
treatment = as.factor(rep(c("HIGH", "MEDIUM", "LOW"), each = 18)),
value = runif(54, 1, 10))
# create the error intervals
d2 <- d1 %>%
dplyr::group_by(time_serie,treatment) %>%
dplyr::summarise(mean_value = mean(value),
SE_value = sd(value/sqrt(length(value)))) %>%
as.data.frame()
# plot
p1 <- ggplot(aes(x = time_serie, y = mean_value, color = treatment, group = treatment), data=d2)
p1
p1a <- p1 + geom_errorbar(aes(ymin = mean_value - SE_value, ymax = mean_value + SE_value), width = .2, position = position_dodge(0.3), size =1) +
geom_point(aes(), position = position_dodge(0.3), size = 3) +
geom_line(aes(color = treatment), position=position_dodge(0.3), size =1)
p1a
Any idea?
Any help would be greatly appreciated :)
Thanks a lot!
Valérian

Answer 1

Up front: this is a partial answer that has two notable issues still to fix (see the end). Edit: the two issues have been resolved, see the far bottom.
I'll change the "dodge" slightly to clarify the point, identify an area of concern, and demonstrate a suggested workaround.
# generate the data
set.seed(244)
d1 <- data.frame(time_serie = as.factor(rep(rep(1:3, each = 6), 3)),
treatment = as.factor(rep(c("HIGH", "MEDIUM", "LOW"), each = 18)),
value = runif(54, 1, 10))
# create the error intervals
d2 <- d1 %>%
dplyr::group_by(time_serie,treatment) %>%
dplyr::summarise(mean_value = mean(value),
SE_value = sd(value/sqrt(length(value)))) %>%
dplyr::arrange(desc(treatment)) %>%
as.data.frame()
# plot
ggplot(aes(x = time_serie, y = mean_value, color = treatment, group = treatment), data=d2) +
geom_errorbar(aes(ymin = mean_value - SE_value, ymax = mean_value + SE_value),
width = 0.2, position = position_dodge(0.03), size = 2) +
geom_point(aes(), position = position_dodge(0.03), size = 3) +
geom_line(aes(color = treatment), position = position_dodge(0.03), size = 2)
Namely, I'll assume that we want HIGH (red) points/lines/error-bars as the top-most layer, masked by nothing. We can see a clear violation of this in the right-most bar: the red dot is over the green errorbar but under the green line.
Unless/until there is an aes(layer=..) aesthetic (there is not afaik), you need to add layers one treatment at a time. While one could hard-code this with nine geoms, you can automate this with lapply. Note that ggplot(.) + list(geom1,geom2,geom3) works just fine, even with nested lists.
I'll control the order of layers with rev(levels(d2$treatment)), assuming that you want LOW as the bottom-most layer (ergo added first). The order of geoms within the list is what defines their layers. Technically we still have a single treatment's errorbar, point, and line on different layers, but they are consecutive so appear to be the same.
ggplot(aes(x = time_serie, y = mean_value, color = treatment, group = treatment), data=d2) +
lapply(rev(levels(d2$treatment)), function(trtmnt) {
list(
geom_errorbar(data = ~ subset(., treatment == trtmnt),
aes(ymin = mean_value - SE_value, ymax = mean_value + SE_value),
width = 0.2, position = position_dodge(0.03), size = 2),
geom_point(data = ~ subset(., treatment == trtmnt), aes(), position = position_dodge(0.03), size = 3),
geom_line(data = ~ subset(., treatment == trtmnt), position = position_dodge(0.03), size = 2)
)
})
(Side note: I use levels(d2$treatment) and data=~subset(., treatment==trtmnt) here, but that's just one way to do it. Another would be lapply(split(d2, d2$treatment), function(x) ...) and use data=x in all of the inner geoms. This latter method allows for multi-variable grouping, if desired. I see no immediate advantage to one over the other.)
The problems with this:
The order of the legend is not consistent with the order of levels of the factor, somehow that is lost. (To be clear, I don't demonstrate this very well here: I can move "medium" to the middle of the legend using levels<-, and it works with the non-lapply rendering code with incorrect layering, but it is again lost with the lapply-geoms.)
position_dodge no longer has awareness of the other treatments, so it does not dodge the other errorbars. The only way around this (not demonstrated here) would be to manually dodge before plotting, shown below.
1: Order of legend elements
This one was solved in lapply'd geoms lose factor-ordering, where we just need to add scale_color_discrete(drop=FALSE).
2: Dodging
The dodge issue can be fixed by using real numerics in the x aesthetic. This is kind of a hack, as it is no longer done by ggplot2 but controlled externally. It's also applying an offset and not dodging, per se. But it does get the desired results.
d2$time_serie2 <- as.integer(as.character(d2$time_serie)) + as.numeric(d2$treatment)/10
ggplot(aes(x = time_serie2, y = mean_value, color = treatment, group = treatment), data = d2) +
lapply(rev(levels(d2$treatment)), function(trtmnt) {
list(
geom_errorbar(data = ~ subset(., treatment == trtmnt),
aes(ymin = mean_value - SE_value, ymax = mean_value + SE_value),
width = 0.2, size = 2),
geom_point(data = ~ subset(., treatment == trtmnt), aes(), size = 3),
geom_line(data = ~ subset(., treatment == trtmnt), size = 2)
)
}) +
scale_color_discrete(drop = FALSE)