Hanne Oberman

There are some solutions: using the `I()` function, transforming the data, or using one of the `scale_*()` functions.

Add examples from issue #10 to vignette

From vignette markdown file: ``` # TODO add to vignette: # plotting conditional on missingness indicator # adding jitter to categorical variables # plotting a single imp # plotting all...

The problem is as follows: The missing data points are not plotted on top of the axes when jitter is used. ``` r library(ggmice) library(ggplot2) ggmice(mice::nhanes, aes(age, bmi)) + geom_point()...

Current code coverage = 82%. Please feel free to add some use cases!

For example, test whether `plot_pred()` works if `blocks` are defined

Test if all functions work when the data has variable names that are used internally as well. For example, `.where` is used for the missingness indicator, but what if it's...

Last version: https://github.com/amices/ggmice/blob/b861dbf94dee7752a9b9581f8674fd6e8029e333/R/plot_variance.R

This would not get the expected density plots, which would then require adding `aes(fill = NULL)` to `geom_density()`

Consider importing `ggplot2` functions