associationsDiamondPlot
This function produces is a diamondplot that plots the confidence intervals for associations between a number of covariates and a criterion. It currently only supports the Pearson's r effect size metric; other effect sizes are converted to Pearson's r.
associationsToDiamondPlotDf is a helper function that produces the required dataframe.
 Keywords
 hplot
Usage
associationsDiamondPlot(dat, covariates, criteria,
labels = NULL,
criteriaLabels = NULL,
decreasing=NULL,
sortBy=NULL,
conf.level=.95,
criteriaColors = brewer.pal(8, 'Set1'),
criterionColor = 'black',
returnLayerOnly = FALSE,
esMetric = 'r',
multiAlpha=.33,
singleAlpha = 1,
showLegend=TRUE,
xlab="Effect size estimates",
ylab="",
theme=theme_bw(),
lineSize = 1,
outputFile = NULL,
outputWidth = 10,
outputHeight = 10,
ggsaveParams = list(units='cm',
dpi=300,
type="cairo"),
...)
associationsToDiamondPlotDf(dat, covariates, criterion, labels = NULL,
decreasing = NULL, conf.level = 0.95,
esMetric = "r")
Arguments
 dat
 The dataframe containing the relevant variables.
 covariates
 The covariates: the list of variables to associate to the criterion or criteria, usually the predictors.
 criteria, criterion

The criteria, usually the dependent variables; one criterion (one dependent variable) can also be specified of course. The helper function
associationsToDiamondPlotDf
always accepts only one criterion.  labels
 The labels for the covariates, for example the questions that were used (as a character vector).
 criteriaLabels
 The labels for the criteria (in the legend).
 decreasing

Whether to sort the covariates by the point estimate of the effect size
of their association with the criterion. Use
NULL
to not sort at all,TRUE
to sort in descending order, andFALSE
to sort in ascending order.  sortBy
 When specifying multiple criteria, this can be used to indicate by which criterion the items should be sorted (if they should be sorted).
 conf.level
 The confidence of the confidence intervals.
 criteriaColors, criterionColor

The colors to use for the different associations can be specified in
criteriaColors
. This should be a vector of valid colors with at least as many elements as criteria are specified incriteria
. If only one criterion is specified, the color incriterionColor
is used.  returnLayerOnly
 Whether to return the entire object that is generated, or just the resulting ggplot2 layer.
 esMetric
 The effect size metric to plot  currently, only 'r' is supported, and other values will return an error.
 multiAlpha, singleAlpha

The transparency (alpha channel) value of the diamonds for each association can be specified in
multiAlpha
, and if only one criterion is specified, the alpha level of the diamonds can be specified insingleAlpha
.  showLegend
 Whether to show the legend.
 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
ggplot
theme to use.  lineSize
 The thickness of the lines (the diamonds' strokes).
 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
and eventually toggDiamondLayer
.
Details
This function can be used to quickly plot multiple confidence intervals.
Value
A plot.
See Also
Examples
### Simple diamond plot with correlations
### and their confidence intervals
associationsDiamondPlot(mtcars,
covariates=c('cyl', 'hp', 'drat', 'wt',
'am', 'gear', 'vs', 'carb', 'qsec'),
criteria='mpg');
### Same diamond plot, but now with two criteria,
### and colouring the diamonds based on the
### correlation point estimates: a gradient
### is created where red is used for 1,
### green for 1 and blue for 0.
associationsDiamondPlot(mtcars,
covariates=c('cyl', 'hp', 'drat', 'wt',
'am', 'gear', 'vs', 'carb', 'qsec'),
criteria=c('mpg', 'disp'),
generateColors=c("red", "blue", "green"),
fullColorRange=c(1, 1));
Community examples
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