meansComparisonDiamondPlot
These are two diamond plot functions to conveniently make diamond plots to compare subgroups or different samples. They are both based on a univariate diamond plot where colors are used to distinguish the data points and diamonds of each subgroup or sample. The means comparison diamond plot produces only this plot, while the duo comparison diamond plot combines it with a diamond plot visualising the effect sizes of the associations. The latter currently only works for two subgroups or samples, while the simple meansComparisonDiamondPlot also works when comparing more than two sets of datapoints. These functions are explained more in detail in Peters (2017).
Usage
meansComparisonDiamondPlot(dat, items = NULL,
compareBy = NULL,
labels = NULL,
compareByLabels = NULL,
decreasing = NULL,
sortBy = NULL,
conf.level = 0.95,
showData = TRUE,
dataAlpha = 0.1, dataSize = 3,
comparisonColors = brewer.pal(8, "Set1"),
alpha = 0.33,
jitterWidth = 0.5, jitterHeight = 0.4,
xlab = "Scores and means",
ylab = NULL,
theme = theme_bw(),
showLegend = TRUE,
lineSize = 1,
xbreaks = "auto",
outputFile = NULL,
outputWidth = 10,
outputHeight = 10,
ggsaveParams = list(units='cm',
dpi=300,
type="cairo"),
...)
duoComparisonDiamondPlot(dat, items = NULL,
compareBy = NULL,
labels = NULL,
compareByLabels = NULL,
decreasing = NULL,
conf.level = c(0.95, 0.95),
showData = TRUE,
dataAlpha = 0.1,
dataSize = 3,
comparisonColors = brewer.pal(8, "Set1"),
associationsColor = "grey",
alpha = 0.33,
jitterWidth = 0.5, jitterHeight = 0.4,
xlab = c("Scores and means", "Effect size estimates"),
ylab = c(NULL, NULL),
theme = theme_bw(),
showLegend = TRUE,
lineSize = 1,
drawPlot = TRUE,
xbreaks = "auto",
outputFile = NULL,
outputWidth = 10,
outputHeight = 10,
ggsaveParams = list(units='cm',
dpi=300,
type="cairo"),
...)
Arguments
 dat
 The dataframe containing the relevant variables.
 items
 The variables to plot (on the y axis).
 compareBy
 The variable by which to compare (i.e. the variable indicating to which subgroup or sample a row in the dataframe belongs).
 labels

The labels to use on the y axis; these values will replace the variable names in the dataframe (specified in
items
).  compareByLabels

The labels to use to replace the value labels of the
compareBy
variable.  decreasing

Whether to sort the variables by their mean values (
NULL
to not sort,TRUE
to sort in descending order (i.e. items with lower means are plotted more to the bottom), andFALSE
to sort in ascending order (i.e. items with lower means are plotted more to the top).  sortBy

If the variables should be sorted (see
decreasing
), this variable specified which subgroup should be sorted by. Therefore, the value specified here must be a value label ('level label') of thecomparisonBy
variable.  conf.level

The confidence level of the confidence intervals specified by the diamonds for the means (for
meansComparisonDiamondPlot
) and for both the means and effect sizes (forduoComparisonDiamondPlot
).  showData
 Whether to plot the data points.
 dataAlpha
 The transparency (alpha channel) value for the data points: a value between 0 and 1, where 0 denotes complete transparency and 1 denotes complete opacity.
 dataSize
 The size of the data points.
 comparisonColors
 The colors to use for the different subgroups or samples. This should be a vector of valid colors with at least as many elements as sets of data points that should be plotted.
 associationsColor

For
duoComparisonDiamondPlot
, the color to use to plot the effect sizes in the righthand plot.  alpha
 The alpha channel (transparency) value for the diamonds: a value between 0 and 1, where 0 denotes complete transparency and 1 denotes complete opacity.
 jitterWidth, jitterHeight
 How much noise to add to the data points (to prevent overplotting) in the horizontal (x axis) and vertical (y axis) directions.
 xlab, ylab

The label to use for the x and y axes (for
duoComparisonDiamondPlot
, must be vectors of two elements). UseNULL
to not use a label.  theme
 The theme to use for the plots.
 showLegend
 Whether to show the legend (which color represents which subgroup/sample).
 lineSize
 The thickness of the lines (the diamonds' strokes).
 drawPlot
 Whether to draw the plot, or only (invisibly) return it.
 xbreaks
 Where the breaks (major grid lines, ticks, and labels) on the x axis should be.
 outputFile
 A file to which to save the plot.
 outputWidth, outputHeight

Width and height of saved plot (specified in centimeters by default, see
ggsaveParams
).  ggsaveParams
 Parameters to pass to ggsave when saving the plot.
 …

Any additional arguments are passed to
diamondPlot
bymeansComparisonDiamondPlot
and to bothmeansComparisonDiamondPlot
andassociationsDiamondPlot
byduoComparisonDiamondPlot
.
Details
These functions are explained in Peters (2017).
Value
Diamond plots: a ggplot
by meansComparisonDiamondPlot
, and a gtable
by duoComparisonDiamondPlot
.
References
Peters, G.J. Y. (2017). Diamond Plots: a tutorial to introduce a visualisation tool that facilitates interpretation and comparison of multiple sample estimates while respecting their inaccuracy. PsyArXiv. http://doi.org/10.17605/OSF.IO/9W8YV
See Also
Examples
meansComparisonDiamondPlot(mtcars,
items=c('disp', 'hp'),
compareBy='vs',
xbreaks=c(100,200, 300, 400));
meansComparisonDiamondPlot(chickwts,
items='weight',
compareBy='feed',
xbreaks=c(100,200,300,400),
showData=FALSE);
duoComparisonDiamondPlot(mtcars,
items=c('disp', 'hp'),
compareBy='vs',
xbreaks=c(100,200, 300, 400));