vpc: Visual predictive checks

In guiastrennec/ggxpose: Diagnostics for Pharmacometric Models

Visual predictive checks

Description

Generate visual predictive checks (VPC)

Usage

vpc(
  xpdb,
  vpc_type = NULL,
  mapping = NULL,
  smooth = TRUE,
  type = "alpr",
  title = "Visual predictive checks | @run",
  subtitle = "Number of simulations: @vpcnsim, confidence interval: @vpcci%",
  caption = "@vpcdir",
  tag = NULL,
  log = NULL,
  guide = TRUE,
  gg_theme,
  xp_theme,
  facets,
  quiet,
  area_fill = c("steelblue3", "grey60", "steelblue3"),
  line_linetype = c("93", "solid", "93"),
  ...
)

Arguments

xpdb	An xpose database object.
vpc_type	Only used when multiple vpc data are present in the same xpdb. The type of vpc to be created. Can be one of can be one of: 'continuous', 'categorical', 'censored' or 'time-to-event'.
mapping	List of aesthetics mappings to be used for the xpose plot (e.g. point_color).
smooth	Should the bins be smoothed (connect bin midpoints, default) or shown as rectangular boxes.
type	String setting the type of plot to be used. Can be points 'p', line 'l', area 'a', rug 'r' and text 't' or any combination of the five.
title	Plot title. Use NULL to remove.
subtitle	Plot subtitle. Use NULL to remove.
caption	Page caption. Use NULL to remove.
tag	Plot identification tag. Use NULL to remove.
log	String assigning logarithmic scale to axes, can be either ”, 'x', y' or 'xy'.
guide	Enable guide display in vpc continuous (e.g. lloq and uloq lines).
gg_theme	A complete ggplot2 theme object (e.g. theme_classic), a function returning a complete ggplot2 theme, or a change to the current gg_theme.
xp_theme	A complete xpose theme object (e.g. theme_xp_default) or a list of modifications to the current xp_theme (e.g. list(point_color = 'red', line_linetype = 'dashed')).
facets	Either a character string to use facet_wrap or a formula to use facet_grid.
quiet	Logical, if FALSE messages are printed to the console.
area_fill	Shaded areas filling color, should be a vector of 3 values (i.e. low, med, high).
line_linetype	Lines linetype, should be a vector of 3 values (i.e. low, med, high).
...	any additional aesthetics.

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. point_color = 'blue', area_fill = 'green', etc.

• point: options to geom_point

• line: options to geom_line

• area: options to geom_ribbon (smooth = TRUE) or geom_rect (smooth = FALSE)

• rug: options to geom_rug

• text: options to geom_text

• guide: options to geom_hline

• xscale: options to scale_x_continuous or scale_x_log10

• yscale: options to scale_y_continuous or scale_y_log10

Faceting

Every xpose plot function has built-in faceting functionalities. Faceting arguments are passed to the functions facet_wrap_paginate when the facets argument is a character string (e.g. facets = c('SEX', 'MED1')) or facet_grid_paginate when facets is a formula (e.g. facets = SEX~MED1). All xpose plot functions accept all the arguments for the facet_wrap_paginate and facet_grid_paginate functions e.g. dv_vs_ipred(xpdb_ex_pk, facets = SEX~MED1, ncol = 3, nrow = 3, page = 1, margins = TRUE, labeller = 'label_both').

Faceting options can either be defined in plot functions (e.g. dv_vs_ipred(xpdb_ex_pk, facets = 'SEX')) or assigned globally to an xpdb object via the xp_theme (e.g. xpdb <- update_themes(xpdb_ex_pk, xp_theme = list(facets = 'SEX'))). In the latter example all plots generate from this xpdb will automatically be stratified by 'SEX'.

By default, some plot functions use a custom stratifying variable named 'variable', e.g. eta_distrib(). When using the facets argument, 'variable' needs to be added manually e.g. facets = c('SEX', 'variable') or facets = c('SEX', 'variable'), but is optional, when using the facets argument in xp_theme variable is automatically added whenever needed.

Template titles

Template titles can be used to create highly informative diagnostics plots. They can be applied to any plot title, subtitle, caption and tag. Template titles are defined via a single string containing key variables staring with a '@' (e.g. '@ofv') which will be replaced by their actual value when rendering the plot. For example ''@run, @nobs observations in @nind subjects'' would become ''run001, 1022 observations in 74 subjects''. The available key variables are listed under template_titles.

See Also

vpc_data

Examples

xpdb_ex_pk %>% 
 vpc_data(opt = vpc_opt(n_bins = 7)) %>% 
 vpc()

guiastrennec/ggxpose documentation built on June 8, 2024, 3:22 p.m.