ggmice

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So `imp$predictorMatrix` is plotted, potentially with `imp$method`

hanneoberman

Automatically group by `.imp` if `group = NULL` in `ggmice()`

2

``` r library(ggmice) library(mice) #> Warning: package 'mice' was built under R version 4.3.1 #> #> Attaching package: 'mice' #> The following objects are masked from 'package:ggmice': #> #> bwplot,...

hanneoberman

Create general pre-processing function for internal use

6

hanneoberman

group by .imp if group=NULL

1

Resolves #133. It may be useful to mention this in the documentation

pepijnvink

Wrapper function for density plots

1

Hey, Hanne! I created a `ggplot2` version of the `mice` density diagnostic plots for a paper I am writing. When I thought about using `ggmice` I had already dedicated quite...

EdoardoCostantini

Plot missing data indicator matrix

4

version 1. visualization based on plot_pattern code

pepijnvink

Plot missingness proportion in categorical variable levels

1

Add plot_groups.R as supposed in #60 which might be serve as a starting point for #66. Note: this function was largely inspired by the `plot_cor()` function that was already part...

rjverheijden

Plot variance of predicted values after imputation

9

gerko's new var plot idea

KyuriP

Create `verify_vrb` utils function

1

``` vrb

hanneoberman

Add `facets` or `purrr::map()` to old friends to plot all variables

4

This is still an advantage of `mice::stripplot(imp)` over the `ggmice` solution

hanneoberman