plot_observed_profiles: Spaghetti plot

In pnolain/pmxploit: Pharmacometric tools for post-processing of mixed-effects models for continuous data

Spaghetti plot

Description

Plot of observed profiles versus an independent variable (e.g. TIME or TAD).

Usage

plot_observed_profiles(
  run,
  compartment = NULL,
  idv = "TIME",
  ids = NULL,
  show_mdv = TRUE,
  log_dv = FALSE,
  mean_profiles = FALSE,
  x_scale = "linear",
  y_scale = "linear",
  logticks_annotation = TRUE,
  facetted = TRUE,
  facet_scales = "free",
  transparency = FALSE,
  auto_legend = TRUE
)

Arguments

run	pmxploit NONMEM run object.
compartment	integer. Number of the compartment of the dependent variable.
idv	character. Name of the column used as independent variable. Default is "TIME".
ids	integer vector of the IDs of the individuals to plot. Default is NULL, plotting all the individuals.
log_dv	logical. Set it to TRUE is dependent variable is in log-scale in the dataset. Default is FALSE.
mean_profiles	logical. If TRUE, summarizes individual profiles by the mean profile (in each group if split_by is specified).
x_scale	character. X-axis scale, one of "linear" or "log". Default is "linear".
y_scale	character. Y-axis scale, one of "linear" or "log". Default is "linear".
logticks_annotation	logical. If x_scale and/or y_scale are "log", adds ticks annotation on the axis.
facetted	logical. If TRUE (default) and split_by is specified, plot each group in a separate facet. Otherwise, draw groups in different colours.
facet_scales	character. ggplot2 facet scales. Default is "free".
transparency	logical. Plot scatterplot dots with transparency, useful to avoid overplotting with large datasets. Default is FALSE.
auto_legend	logical. When TRUE (default), default pmxploit plotting options are applied (title, labels, axis...).

Value

A ggplot2 object.

Examples

EXAMPLERUN %>% plot_observed_profiles(compartment = 2)

EXAMPLERUN %>% group_by(CMT) %>% plot_observed_profiles(compartment = 2:3)

EXAMPLERUN %>% group_by(SEX) %>% plot_observed_profiles(compartment = 2)
EXAMPLERUN %>% group_by(SEX) %>% plot_observed_profiles(compartment = 2, facetted = FALSE)

EXAMPLERUN %>% group_by(SEX) %>% plot_observed_profiles(compartment = 2, mean_profiles = TRUE)
EXAMPLERUN %>% group_by(SEX) %>%
  plot_observed_profiles(compartment = 2, mean_profiles = TRUE, facetted = FALSE)

EXAMPLERUN %>%
  group_by(SEX) %>%
  plot_observed_profiles(compartment = 2, y_scale = "log", facetted = FALSE)

pnolain/pmxploit documentation built on Jan. 31, 2024, 1:16 p.m.