Plot Residuals against a continuous or categorical covariate.

res_vs_cov(
  xpdb,
  mapping = NULL,
  covariate,
  res = "CWRES",
  group = "ID",
  type = "bpls",
  title = "Residuals vs @x | @run",
  subtitle = "Based on @nind individuals",
  caption = "@dir",
  tag = NULL,
  log = NULL,
  guide = TRUE,
  facets,
  .problem,
  quiet,
  ...
)

Arguments

xpdb

An xpose database object.

mapping

List of aesthetics mappings to be used for the xpose plot (e.g. point_color).

covariate

Character; String of covariate name

res

Character; String of residual name; CWRES by default.

group

Grouping variable to be used for lines. ID by default

type

Character; String setting the type of plot to be used. Must be 'b' for categorical covariates, one or a combination of 'p','l','s' for continuous covariates.

title

Character; Plot title. Use NULL to remove.

subtitle

Character; Plot subtitle. Use NULL to remove.

caption

Character; Page caption. Use NULL to remove.

tag

Character; Plot identification tag. Use NULL to remove.

log

Character; String assigning logarithmic scale to axes, can be either '', 'x', y' or 'xy'.

guide

Logical; Should the guide (e.g. reference distribution) be displayed.

facets

Either a character string to use facet_wrap_paginate or a formula to use facet_grid_paginate.

.problem

The $problem number to be used. By default returns the last estimation problem.

quiet

Logical, if FALSE messages are printed to the console.

...

Any additional aesthetics to be passed on xplot_scatter or xplot_box.

Layers mapping

Plots can be customized by mapping arguments to specific layers. The naming convention is layer_option where layer is one of the names defined in the list below and option is any option supported by this layer e.g. boxplot_fill = 'blue', etc.

  • box plot: options to geom_boxplot

  • point plot: options to geom_point

  • line plot: options to geom_line

  • smooth plot: options to geom_smooth

  • xscale: options to scale_x_continuous or scale_x_log10

  • yscale: options to scale_y_continuous or scale_y_log10

Last Updated By

Michael Tomashevskiy

Last Update Date

2022/12/07

Examples

res_vs_cov(xpose::xpdb_ex_pk,
  covariate = "SEX",
  type = "b",
  res = "WRES"
)
#> Using data from $prob no.1
#> Filtering data by EVID == 0


res_vs_cov(xpose::xpdb_ex_pk,
  covariate = "AGE",
  type = "ps",
  res = c("CWRES", "WRES", "IRES", "IWRES")
)
#> Using data from $prob no.1
#> Filtering data by EVID == 0
#> Tidying data by ID, SEX, MED1, MED2, DOSE ... and 23 more variables
#> `geom_smooth()` using formula = 'y ~ x'
#> `geom_smooth()` using formula = 'y ~ x'