Description Usage Arguments Details Value Examples

The dlvPlot function produces a dot-violin-line plot, and dlvTheme is the default theme.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | ```
dlvPlot(dat, x = NULL, y, z = NULL,
conf.level = .95,
jitter = "FALSE",
binnedDots = TRUE, binwidth=NULL,
error="lines",
dotsize="density",
singleColor = "black",
comparisonColors = brewer.pal(8, 'Set1'),
densityDotBaseSize=3,
normalDotBaseSize=1,
violinAlpha = .2,
dotAlpha = .4,
lineAlpha = 1,
connectingLineAlpha = 1,
meanDotSize=5,
posDodge=0.2,
errorType = "both",
outputFile = NULL,
outputWidth = 10,
outputHeight = 10,
ggsaveParams = list(units='cm',
dpi=300,
type="cairo"))
dlvTheme(base_size = 11, base_family = "", ...)
``` |

`dat` |
The dataframe containing x, y and z. |

`x` |
Character value with the name of the predictor ('independent') variable, must refer to a categorical variable (i.e. a factor). |

`y` |
Character value with the name of the critetion ('dependent') variable, must refer to a continuous variable (i.e. a numeric vector). |

`z` |
Character value with the name of the moderator variable, must refer to a categorical variable (i.e. a factor). |

`conf.level` |
Confidence of confidence intervals. |

`jitter` |
Logical value (i.e. TRUE or FALSE) whether or not to jitter individual datapoints. Note that jitter cannot be combined with posDodge (see below). |

`binnedDots` |
Logical value indicating whether to use binning to display the dots. Overrides jitter and dotsize. |

`binwidth` |
Numeric value indicating how broadly to bin (larger values is more binning, i.e. combining more dots into one big dot). |

`error` |
Character value: "none", "lines" or "whiskers"; indicates whether to show the confidence interval as lines with (whiskers) or without (lines) horizontal whiskers or not at all (none) |

`dotsize` |
Character value: "density" or "normal"; when "density", the size of each dot corresponds to the density of the distribution at that point. |

`singleColor` |
The color to use when drawing one or more univariate distributions (i.e. when no |

`comparisonColors` |
The colors to use when a |

`densityDotBaseSize` |
Numeric value indicating base size of dots when their size corresponds to the density (bigger = larger dots). |

`normalDotBaseSize` |
Numeric value indicating base size of dots when their size is fixed (bigger = larger dots). |

`violinAlpha` |
Numeric value indicating alpha value of violin layer (0 = completely transparent, 1 = completely opaque). |

`dotAlpha` |
Numeric value indicating alpha value of dot layer (0 = completely transparent, 1 = completely opaque). |

`lineAlpha` |
Numeric value indicating alpha value of the confidence interval line layer (0 = completely transparent, 1 = completely opaque). |

`connectingLineAlpha` |
Numeric value indicating alpha value of the layer with the lines connecting the means (0 = completely transparent, 1 = completely opaque). |

`meanDotSize` |
Numeric value indicating the size of the dot used to indicate the mean in the line layer. |

`posDodge` |
Numeric value indicating the distance to dodge positions (0 for complete overlap). |

`errorType` |
If the error is shown using lines, this argument indicates Whether the
errorbars should show the confidence interval ( |

`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. |

`base_size, base_family, ...` |
Passed on to the ggplot theme_grey() function. |

This function creates Dot Violin Line plots. One image says more than a thousand words; I suggest you run the example :-)

The behavior of this function depends on the arguments.

If no x and z are provided and y is a character value, dlvPlot produces a univariate plot for the numerical y variable.

If no x and z are provided, and y is c character vector, dlvPlot produces multiple Univariate plots, with variable names determining categories on x-axis and with numerical y variables on y-axis

If both x and y are a character value, and no z is provided, dlvPlot produces a bivariate plot where factor x determines categories on x-axis with numerical variable y on the y-axis (roughly a line plot with a single line)

Finally, if x, y and z are each a character value, dlvPlot produces multivariate plot where factor x determines categories on x-axis, factor z determines the different lines, and with the numerical y variable on the y-axis

An object is returned with the following elements:

`dat.raw` |
Raw datafile provided when calling dlvPlot |

`dat` |
Transformed (long) datafile dlvPlot uses |

`descr` |
Dataframe with extracted descriptives used to plot the mean and confidence intervals |

`yRange` |
The range of the Y variable used to construct the plot |

`plot` |
The plot itself |

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ```
### Note: the 'not run' is simply because running takes a lot of time,
### but these examples are all safe to run!
## Not run:
### Create simple dataset
dat <- data.frame(x1 = factor(rep(c(0,1), 20)),
x2 = factor(c(rep(0, 20), rep(1, 20))),
y=rep(c(4,5), 20) + rnorm(40));
### Generate a simple dlvPlot of y
dlvPlot(dat, y='y');
### Now add a predictor
dlvPlot(dat, x='x1', y='y');
### And finally also a moderator:
dlvPlot(dat, x='x1', y='y', z='x2');
### The number of datapoints might be a bit clearer if we jitter
dlvPlot(dat, x='x1', y='y', z='x2', jitter=TRUE);
### Although just dodging the density-sized dots might work better
dlvPlot(dat, x='x1', y='y', z='x2', posDodge=.3);
## End(Not run)
``` |

```
Registered S3 method overwritten by 'GGally':
method from
+.gg ggplot2
Registered S3 methods overwritten by 'lme4':
method from
cooks.distance.influence.merMod car
influence.merMod car
dfbeta.influence.merMod car
dfbetas.influence.merMod car
Warning message:
`fun.y` is deprecated. Use `fun` instead.
Warning message:
`fun.y` is deprecated. Use `fun` instead.
Warning message:
`fun.y` is deprecated. Use `fun` instead.
Warning message:
`fun.y` is deprecated. Use `fun` instead.
```

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.