xpose.xtras (version 0.2.2)

eta_vs_catcov: Eta categorical covariate plots (typical)

Description

Eta categorical covariate plots (typical)

Usage

eta_vs_catcov(
  xpdb,
  mapping = NULL,
  etavar = NULL,
  covvar = NULL,
  drop_fixed = TRUE,
  orientation = "x",
  show_n = check_xpdb_x(xpdb, .warn = FALSE),
  type = "bol",
  list = TRUE,
  title = "Eta versus categorical covariates | @run",
  subtitle = "Based on @nind individuals, Eta shrink: @etashk",
  caption = "@dir",
  tag = NULL,
  facets,
  .problem,
  quiet,
  ...
)

Value

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

Arguments

xpdb

<xp_xtras> or <xpose_data`> object

mapping

ggplot2 style mapping

etavar

tidyselect for eta 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 etavar resolves to more than one eta. If TRUE (default, for backwards compatibility), returns a plain list of one plot per eta. If FALSE, all etas are instead combined onto one shared plot -- faceted by eta, 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.

Details

The ability to show number per covariate level is inspired by the package pmplots, but is implements here within the xpose ecosystem for consistency.

Examples

# \donttest{

eta_vs_catcov(xpdb_x)

# Labels and units are also supported
xpdb_x %>%
  xpose::set_var_labels(AGE="Age", MED1 = "Digoxin") %>%
  xpose::set_var_units(AGE="yrs") %>%
  set_var_levels(SEX=lvl_sex(), MED1 = lvl_bin()) %>%
  eta_vs_catcov()

# Combine all etas onto one shared, faceted plot instead of a list
eta_vs_catcov(xpdb_x, list = FALSE)

# Restrict to specific covariates with covvar, just like etavar
eta_vs_catcov(xpdb_x, covvar = SEX)
# }