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.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | ```
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 |

`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 |

`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 |

`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 |

`showLegend` |
Whether to show the legend. |

`xlab, ylab` |
The label to use for the x and y axes (for |

`theme` |
The |

`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` |
Parameters to pass to ggsave when saving the plot. |

`...` |
Any additional arguments are passed to |

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`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
### 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));
``` |

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