Diamond plots

This function generates a so-called diamond plot: a plot based on the forest plots that are commonplace in meta-analyses. The underlying idea is that point estimates are uninformative, and it would be better to focus on confidence intervals. The problem of the points with errorbars that are commonly employed is that the focus the audience's attention on the upper and lower bounds, even though those are the least relevant values. Using diamonds remedies this.

meansDiamondPlot(dat, items = NULL,
                 labels = NULL,
                 decreasing = NULL,
                 conf.level = 0.95,
                 showData = TRUE,
                 dataAlpha = .1,
                 dataSize = 3,
                 dataColor = "#444444",
                 diamondColors = NULL,
                 jitterWidth = 0.5,
                 jitterHeight = 0.4,
                 returnLayerOnly = FALSE,
                 xlab = "Scores and means",
                 ylab = NULL,
                 theme = theme_bw(),
                 xbreaks="auto",
                 outputFile = NULL,
                 outputWidth = 10,
                 outputHeight = 10,
                 ggsaveParams = list(units='cm',
                                     dpi=300,
                                     type="cairo"),
                 ...)

Arguments

dat	The dataframe containing the variables (items) to show in the diamond plot.
items	Optionally, the names (or numeric indices) of the variables (items) to show in the diamond plot. If NULL, all columns (variables, items) will be used.
labels	A character vector of labels to use instead of column names from the dataframe.
decreasing	Whether to sort the variables (rows) in the diamond plot decreasing (TRUE), increasing (FALSE), or not at all (NULL).
conf.level	The confidence of the confidence intervals.
showData	Whether to show the raw data or not.
dataAlpha	This determines the alpha (transparency) of the data points. Note that argument alpha can be used to set the alpha of the diamonds; this is eventually passed on to ggDiamondLayer.
dataSize	The size of the data points.
dataColor	The color of the data points.
diamondColors	A vector of the same length as there are rows in the dataframe, to manually specify colors for the diamonds.
jitterWidth	How much to jitter the individual datapoints horizontally.
jitterHeight	How much to jitter the individual datapoints vertically.
returnLayerOnly	Set this to TRUE to only return the ggplot layer of the diamondplot, which can be useful to include it in other plots.
xlab, ylab	The labels of the X and Y axes.
theme	The theme to use.
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.
…	Additional arguments are passed to diamondPlot and eventually to ggDiamondLayer. This can be used to, for example, specify two or more colors to use to generate a gradient (using generateColors and maybe fullColorRange).

Value

A ggplot plot with a ggDiamondLayer is returned.

See also

diamondPlot, meanSDtoDiamondPlot, factorLoadingDiamondCIplot, ggDiamondLayer

Examples

tmpDf <- data.frame(item1 = rnorm(50, 1.6, 1),
                    item2 = rnorm(50, 2.6, 2),
                    item3 = rnorm(50, 4.1, 3));

### A simple diamond plot
meansDiamondPlot(tmpDf);

### A diamond plot with manually
### specified labels and colors
meansDiamondPlot(tmpDf,
                 labels=c('First',
                          'Second',
                          'Third'),
                  diamondColors=c('blue', 'magenta', 'yellow'));

### Using a gradient for the colors
meansDiamondPlot(tmpDf,
                 labels=c('First',
                          'Second',
                          'Third'),
                 generateColors = c("magenta", "cyan"),
                 fullColorRange = c(1,5));