Shrinkage contribution versus categorical covariates

Mirrors eta_vs_catcov(), but for the per-individual shrinkage contribution diagnostic (shk type columns, see derive_shk()/backfill_shk()) instead of the etas themselves.

Usage

shk_vs_catcov(
  xpdb,
  mapping = NULL,
  shkvar = NULL,
  covvar = NULL,
  drop_fixed = TRUE,
  orientation = "x",
  show_n = check_xpdb_x(xpdb, .warn = FALSE),
  type = "bol",
  list = TRUE,
  title = "Shrinkage contribution versus categorical covariates | @run",
  subtitle = "Based on @nind individuals",
  caption = "@dir",
  tag = NULL,
  facets,
  .problem,
  quiet,
  ...
)

Arguments

xpdb

<xp_xtras> or <xpose_data> object

mapping

ggplot2 style mapping

shkvar

tidyselect for shk variables

covvar

tidyselect for categorical covariate variables; NULL (default) selects every categorical covariate in the xpdb data index.

drop_fixed

As in xpose

orientation

Passed to xplot_boxplot

show_n

Add "N=" to plot

type

Passed to xplot_boxplot

list

<logical> Only relevant when shkvar resolves to more than one shk column. If TRUE (default, for backwards compatibility), returns a plain list of one plot per shk column. If FALSE, they are instead combined onto one shared plot – faceted by shk column, in addition to the existing per-covariate facet – automatically paginating (at most 9 panels per page, i.e. ncol/nrow of 3) via xpose's own facet_wrap_paginate mechanism. Printing the returned plot renders every page; pass page to print() to select a specific one.

title

Plot title

subtitle

Plot subtitle

caption

Plot caption

tag

Plot tag

facets

Additional facets

.problem

Problem number

quiet

Silence output

...

Any additional aesthetics.

Value

The desired plot, or (when shkvar resolves to more than one shk column and list = TRUE) a plain list of one plot per column.

Examples

# \donttest{

xpdb_x %>%
  backfill_shk() %>%
  shk_vs_catcov()
#> Using data from $prob no.1
#> Removing duplicated rows based on: ID
#> Tidying data by ID, DOSE, AMT, SS, II ... and 26 more variables
#> Warning: attributes are not identical across measure variables; they will be dropped
#> Using data from $prob no.1
#> Removing duplicated rows based on: ID
#> Tidying data by ID, DOSE, AMT, SS, II ... and 26 more variables
#> Warning: attributes are not identical across measure variables; they will be dropped
#> Using data from $prob no.1
#> Removing duplicated rows based on: ID
#> Tidying data by ID, DOSE, AMT, SS, II ... and 26 more variables
#> Warning: attributes are not identical across measure variables; they will be dropped
#> [[1]]

#> 
#> [[2]]

#> 
#> [[3]]

#> 

# Combine all shk columns onto one shared, faceted plot instead of a list
xpdb_x %>%
  backfill_shk() %>%
  shk_vs_catcov(list = FALSE)
#> Using data from $prob no.1
#> Removing duplicated rows based on: ID
#> Tidying data by ID, DOSE, AMT, SS, II ... and 26 more variables
#> Warning: attributes are not identical across measure variables; they will be dropped

# }