cr_plot: Create a clinical relevance plot

In saviclab/savictools: Streamlined Data Manipulation for Pharmacometrics

Create a clinical relevance plot

Description

cr_plot() visualizes the clinical relevance of covariate effects.

Usage

cr_plot(
  runno,
  effect_size = 0.2,
  width = 0.95,
  type = "lattice",
  adjust = 1,
  n = 10000,
  ...
)

Arguments

runno	A run number or model name.
effect_size	The effect size needed for clinical relevance. Default is 0.2.
width	Size of the interval of the posterior distribution of covariate effects. Defaults to 0.95, or 95%.
type	Plotting library to use. Either "lattice" (the default) or "ggplot".
adjust	Passed to adjust argument in ggplot2::geom_density.
n	Number of samples to draw from the normal distribution for bootstrapping parameter estimates.
...	Unquoted expressions representing covariate relations; see example.

Details

Using the variance-covariance matrix together with parameter estimates, cr_plot() displays the posterior distributions of covariate effects relative to the range of clinical importance.

Value

No return value, called for side effects

Author(s)

Hwi-yeol (Thomas) Yun, Sandy Floren

Examples

## Not run: 
# WT on V, WAZ on F1, FORMULATION on KA
cr_plot(27, VWT = 1 + THETA(12), WAZF1 = 1 + THETA(11),
        KAFORMULATION = 1 + THETA(9))

## End(Not run)

saviclab/savictools documentation built on Dec. 7, 2023, 11:56 p.m.