associationsDiamondPlot: A diamondplot with confidence intervals for associations
In userfriendlyscience: Quantitative Analysis Made Accessible

Description Usage Arguments Details Value Author(s) See Also Examples

View source: R/associationsDiamondPlot.R

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.

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")

`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`.

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

A plot.

Gjalt-Jorn Peters

Maintainer: Gjalt-Jorn Peters <gjalt-jorn@userfriendlyscience.com>

diamondPlot, ggDiamondLayer, CIBER

### 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));