`R/associationsDiamondPlot.R`

, `R/associationsToDiamondPlotDf.R`

`associationsDiamondPlot.Rd`

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.

```
associationsDiamondPlot(
dat,
covariates,
criteria,
labels = NULL,
criteriaLabels = NULL,
decreasing = NULL,
sortBy = NULL,
conf.level = 0.95,
criteriaColors = viridisPalette(length(criteria)),
criterionColor = "black",
returnLayerOnly = FALSE,
esMetric = "r",
multiAlpha = 0.33,
singleAlpha = 1,
showLegend = TRUE,
xlab = "Effect size estimates",
ylab = "",
theme = ggplot2::theme_bw(),
lineSize = 1,
outputFile = NULL,
outputWidth = 10,
outputHeight = 10,
ggsaveParams = ufs::opts$get("ggsaveParams"),
...
)
associationsToDiamondPlotDf(
dat,
covariates,
criterion,
labels = NULL,
decreasing = NULL,
conf.level = 0.95,
esMetric = "r"
)
```

- 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, and`FALSE`

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 in`criteria`

. If only one criterion is specified, the color in`criterionColor`

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 in`singleAlpha`

.- 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). Use`NULL`

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 to`ggDiamondLayer()`

.

A plot.

associationsToDiamondPlotDf is a helper function that produces the required dataframe.

This function can be used to quickly plot multiple confidence intervals.

```
### 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));
```