geom_superberrorbar for expanded error bar displays

Source: R/geom_superberrorbar.R

geom_superberrorbar() is a geom for ggplots; it is based on the original geom_errorbar (and is totally compatible with it) but expands this geom in four different ways. First, it is possible to decide the error bar tips direction which can be unidirectional, pointing to the "left" or to the "right" or go in "both" directions. Second, it is possible set tipformat to "double" or "triple" the horizontal marks at the extremities of the error bar, with a tipgap of your liking. Third, an additional characteristic is vcolour to set a different colour for the vertical part of the error bar or the pair vcolour and wcolour for the top half and bottom half of the vertical error bar. The colour(s) can also be "NA" to have it invisible. Lastly, the error bar can be pointing "up" and "down" or go in "both" (the default)

geom_superberrorbar(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

(as usual) see geom_errorbar

data

(as usual) see geom_errorbar

stat

(as usual) see geom_errorbar

position

(as usual) see geom_errorbar

...

all additional parameters are sent to the underlying geom_path. Includes

  • pointing (NEW) either "up", "down" or "both" up and down;

  • direction (NEW) "left", "right" or "both" (Default is "both")

  • tipformat (NEW) "single", "double" or "triple" to add additional marker lines to the tips (default is "single")

  • tipgap (NEW) The spacing between the markers when "double" or "triple" is used (default 0.1)

  • vcolour (NEW) for the vertical part of the error bar

  • wcolour (NEW) if specified, for the second half of the vertical part of the error bar.

na.rm

(as usual) see geom_errorbar

orientation

(as usual) see geom_errorbar

show.legend

(as usual) see geom_errorbar

inherit.aes

(as usual) see geom_errorbar

Value

a layer containing error bars in a ggplot object

Examples

library(superb) # to import the geom_superberrorbar
library(ggplot2)

# let's have a fake data frame
dta <- data.frame(grp = c(1,2,3), center=c(1,2,3), width = c(1,1,1.5) )

# an example with none of the new features = a regular error bar
ggplot(dta, aes(ymin=center-width, ymax=center+width, x = grp ) ) +
  geom_superberrorbar()


# an example with left-pointing error bars
ggplot(dta, aes(ymin=center-width, ymax=center+width, x = grp ) ) +
  geom_superberrorbar(direction="left", width = 0.1)


# an example with doubled-tipped error bar and the default tipgap
ggplot(dta, aes(ymin=center-width, ymax=center+width, x = grp ) ) +
  geom_superberrorbar(tipformat = "double", width = 0.1)


# an example with left-pointing tripled-tip error bars with small gaps
ggplot(dta, aes(ymin=center-width, ymax=center+width, x = grp ) ) +
  geom_superberrorbar(tipformat = "triple", width= 0.1, tipgap = 0.04, direction = "left")


# an example with unidirectional error bars (here "up" bars)
ggplot(dta, aes(y= center, ymin=center-width, ymax=center+width, x = grp ) ) +
  geom_bar(stat="identity", fill = "yellow") + 
  geom_superberrorbar(pointing = "up")


# a final example with two-coloured, left-pointing tripled-tip error bars with small gaps
ggplot(dta, aes(ymin=center-width, ymax=center+width, x = grp ) ) +
  geom_superberrorbar(tipformat = "triple", width= 0.1, tipgap = 0.04, direction = "left",
           colour = "black", vcolour = "orange")


# This new geom is integrated inside superb() so that you can vary the 
# error bar shapes. Let's see examples:

# using GRD to generate random data with a moderate effect
options(superb.feedback = 'none') # shut down 'warnings' and 'design' interpretation messages
test <- GRD(SubjectsPerGroup  = 20,
       WSFactors = "Moment(5)", 
            Effects = list("Moment" = extent(10) ),
            Population = list(mean = 100, stddev = 15, rho = 0.8) ) 

ornate = list(
        labs(title =paste("(left)            95% confidence intervals",
                        "\n(right)          99% confidence intervals",
                        "\n(center, up) 99.9% confidence intervals")),
        xlab("Moment"), ylab("Score"),
        coord_cartesian( ylim = c(85,125) )
)

plt1 <- superb(
            crange(DV.1, DV.5) ~ ., 
            test, 
            WSFactors = "Moment(5)",  
            adjustments=list(purpose = "difference", decorrelation = "CA"), 
            errorbarParams = list(direction = "left", color="purple", 
                                  width = 0.2, position = position_nudge(-0.05) ),
            gamma     = 0.95,
            plotStyle = "line" ) + ornate
plt2 <- superb( 
            crange(DV.1, DV.5) ~ ., 
            test, 
            WSFactors = "Moment(5)",  
            adjustments=list(purpose = "difference", decorrelation = "CA"), 
            errorbarParams = list(direction = "right", tipgap = 0.25, tipformat = "double", 
                                  width = 0.2, position = position_nudge(+0.05) ),
            gamma     = 0.99,
            plotStyle = "line" ) + ornate 
plt3 <- superb( 
            crange(DV.1, DV.5) ~ ., 
            test, 
            WSFactors = "Moment(5)",  
            adjustments=list(purpose = "difference", decorrelation = "CA"), 
            errorbarParams = list(direction = "both", tipformat = "single", pointing="up", 
                                  width = 0.2, position = position_nudge(0) ),
            gamma     = 0.999,
            plotStyle = "line" ) + ornate 

# transform the ggplots into "grob" so that they can be manipulated
plt1 <- ggplotGrob(plt1)
plt2 <- ggplotGrob(plt2 + makeTransparent() )
plt3 <- ggplotGrob(plt3 + makeTransparent() )

# put the grobs onto an empty ggplot 
ggplot() + 
    annotation_custom(grob=plt1) + 
    annotation_custom(grob=plt2) + 
    annotation_custom(grob=plt3)



# all of them as aesthetics
set.seed(1)
library(dplyr)
#> Warning: package 'dplyr' was built under R version 4.3.3
#> 
#> Attaching package: 'dplyr'
#> The following object is masked from 'package:gridExtra':
#> 
#>     combine
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
dat <- data.frame(Trial = c(rep("Pre",9),rep("Post",9)), 
                     Time = rep.int(seq(0,120,15),2), 
                     var = c(rnorm(9,15,2),rnorm(9,22,2)),
                     var_sd = c(rnorm(18,3,1)))
dat <- mutate(dat, point = ifelse(Trial == "Pre","down","up"))
dat <- mutate(dat, direc = ifelse(Trial == "Pre","left","right"))
dat <- mutate(dat, tipfo = ifelse(Trial == "Pre","double","triple"))
dat <- mutate(dat, vcolo = ifelse(Trial == "Pre","red","blue"))
   
ggplot(data = dat, 
       aes(x = Time, y = var, group = Trial)) +
   geom_line(aes(linetype = Trial)) +  
   geom_point(aes(shape= Trial, fill = Trial), size=2) +
   geom_superberrorbar(aes(ymin=var-var_sd, 
                           ymax=var+var_sd,
                           direction = direc,
                           pointing = point, 
                           wcolour = vcolo,  
                           vcolour = "green",
                           tipformat = tipfo
       ), 
       width = 4)