ggPMX v0.9.4

'ggplot2' Based Tool to Facilitate Diagnostic Plots for NLME Models

At Novartis, we aimed at standardizing the set of diagnostic plots used for modeling activities in order to reduce the overall effort required for generating such plots. For this, we developed a guidance that proposes an adequate set of diagnostics and a toolbox, called 'ggPMX' to execute them. 'ggPMX' is a toolbox that can generate all diagnostic plots at a quality sufficient for publication and submissions using few lines of code.

Readme

ggPMX R package

$CRAN\_Status\_Badge$

ggPMX is an open-source R package freely available on CRAN since April 2019. It generates standard diagnostic plots for mixed effect models used in pharmacometric activities. The package builds on the R-package ggplot2 and aims at providing a workflow that is consistent, reproducible and efficient, resulting in high quality graphics ready-to-use in submission documents and publications. Intuitive functions and options allow for optimal figure customization and graphics stratification. ggPMX enables straightforward generation of PDF, Word or PNG output files that contain all diagnostic plots for keeping track of modeling results. The package is currently compatible with Monolix versions 2016 and 2018R1.

Using simple syntax, the toolbox produces various goodness-of-fit diagnostics such as:

residual- and empirical Bayes estimate (EBE)-based plots,
distribution plots,
prediction- and simulation-based diagnostics (visual predictive checks).

In addition, shrinkage and summary parameters tables can be also produced. By default, the PDF- or Word-format diagnostic report contains essential goodness-of-fit plots. However, these can be adapted to produce different sets of diagnostics as desired by the user, and any of the plots may be customized individually. The types of supported customizations include modifications of the graphical parameters, labels, and various stratifications by covariates.

Documentation

Vignette

Install ggPMX

CRAN:

install.packages("ggPMX")

Github version:

devtools::install_github("ggPMXdevelopment/ggPMX")

Feedback

ggPMX is now ready for inputs and enhancements by the pharmacometric community.

Please use package issues to fill in your feedback.

Functions in ggPMX

Name	Description
FacetWrapPaginate	Extend facet_wrap using ggproto
eta_cov	This creates an ETA covariance matrix which can be used to define the co-relation between the parameters and its shrinkage..
facet_wrap_paginate	Split facet_wrap over multiple plots
eta_pairs	This creates an eta correlation which defines the relationship between parameters
eta_distribution_plot	Eta distribution plots
distrib	creates a graphic distribution object
add_draft	Add draft layer annotation
eta_cov_plot	Eta Covariates plots
getPmxOption	Get ggPMX Option
abbrev	Give the whole abbreviation definition
get_abbrev	Get abbreviation definition by key
get_data	Get controller data set
parse_mlxtran	Parse MONOLIX mlxtran file
n_pages	Determine the number of pages in a paginated facet plot
gtable_remove_grobs	Remove named elements from gtable
individual	This function can be used to obtain individual prediction and compare with observed data and population prediction for each individual separately
get_plot_config	Get the plot config by name
get_plot	Get plot object
plot_pmx.individual	This function can be used to plot individual prediction and compare with observed data and population prediction for each individual separately
plot_pmx.eta_pairs	Plot random effect correlation plot
get_conts	Get continuous covariates
is.pmx_gpar	Check if an object is a pmx_gpar class
get_occ	Get controller occasional covariates
plot_names	Get plot names
pmx_bloq	Creates BLOQ object attributes
input_finegrid	Merge input and fingrid data sets
pk_occ	Creates pmx controller using monlix data having Occasional variable
pk_pd	Creates pkpd pmx controller using package internal data
get_covariates	Get covariates variables
get_cats	Get category covariates
plot_pmx	This is a generic plot method that produces all plots by default described in pmx model evaluation guidance.
get_strats	Get extra stratification variables
pmx_comp_shrink	Compute Shrinkage
pmx_gpar	Handling pmx Graphical parameters
pmx_theme	Define ggPMX theme
print.configs	This function can be used to print configuration of the defined object using S3 method.
print.pmxClass	Print pmxClass object
pmx_get_configs	Get List of built-in configurations
pmx_sim	Create simulation object
l_left_join	Merge 2 lists
ggPMX	ggPMX: A ggplot2 toolbox for Nonlinear Mixed-Effect Model graphical
pmx	Create a pmx object
load_config	Obtain the data source config
pmxOptions	This function can be used to set ggPMX options
pmx_register_plot	Register plot
pmx_plot_individual	Individual plot
pmx_plot_eta_matrix	Eta matrix plot
plot_pmx.pmx_qq	This function plot EBE versus covariates using qq plots
load_data_set	Load data set
pmx_plot	Generic pmx plot
load_source	Load all/or some source data set
plot_pmx.distrib	Plot EBE distribution
plot_pmx.residual	This function plots residual for each observed value by finding the difference between observed and predicted points. It also fits a distribution to the residual value.
plot_pmx.pmx_dens	This function plot EBE versus covariates using qq plots
plot_shrink	Plot shrink in eta matric
plots	Get plots description
pmx_endpoint	Creates pmx endpoint object
plot_pmx.pmx_gpar	The ggPMX base plot function
print.pmxConfig	S3 method print pmxConfig object
[.pmx_gpar	Method for subsetting "pmx_gpar" objects
pmx_config	This function can be used to define the pmx configuration used in plots. e.g. Monolox/Nonmem
pmx_copy	Creates a deep copy of the controller
print.pmx_gpar	Print pmx_gpar object
pmx_plot_cats	Generic pmx stratified plot
pmx_plot_iwres_dens	IWRES density plot
reexports	Objects exported from other packages
pmx_plot_vpc	VPC plot
pmx_vpc_obs	Sets vpc observation layer
residual	This function create a residual for each observed value and also generates a residual distribution
pmx_filter	filter data in a pmx controller
theophylline	Creates pmx controller using theophylline data
pmx_vpc_bin	Creates vpc bins
set_abbrev	update or add a new abbreviation
pmx_report	Generates ggpmX report from a pre-defined template
pmx_vpc_ci	Sets vpc confidence interval layer
residual_scatter	Scatter residual plots
pmx_report_template	Gets build-in report templates
pmx_update	Update plot object
pmx_settings	Create controller global settings
pmx_vpc	Creates vpc object
read_input	Read Modelling input data
pmx_dens	Creates a density plot object
pmx_cov	Select/Map covariates using human labels
plot_pmx.eta_cov	This plots an ETA covariance matrix which can be used to define the co-relation between the parameters and its shrinkage
print.abbreviation	S3 print abbreviation
pmx_qq_plot	Quantile-quantile plots
pmx_vpc_rug	Sets vpc rug layer
pmx_qq	This function creates a qq plot object
read_mlx_par_est	Read MONOLIX parameter estimation file
pmx_vpc_pi	Sets vpc percentile layer
read_mlx_ind_est	Read MONOLIX individual parameters
set_data	Set a controller data set
set_plot	Create a new plot of the desired type
read_mlx_pred	Read MONOLIX model predictions
wrap_formula	merge facets formula with new formula
No Results!

Name

Description

FacetWrapPaginate

Extend facet_wrap using ggproto

eta_cov

This creates an ETA covariance matrix which can be used to define the co-relation between the parameters and its shrinkage..

facet_wrap_paginate

Split facet_wrap over multiple plots

eta_pairs

This creates an eta correlation which defines the relationship between parameters

eta_distribution_plot

Eta distribution plots

distrib

creates a graphic distribution object

add_draft

Add draft layer annotation

eta_cov_plot

Eta Covariates plots

getPmxOption

Get ggPMX Option

abbrev

Give the whole abbreviation definition

get_abbrev

Get abbreviation definition by key

get_data

Get controller data set

parse_mlxtran

Parse MONOLIX mlxtran file

n_pages

Determine the number of pages in a paginated facet plot

gtable_remove_grobs

Remove named elements from gtable

individual

This function can be used to obtain individual prediction and compare with observed data and population prediction for each individual separately

get_plot_config

Get the plot config by name

get_plot

Get plot object

plot_pmx.individual

This function can be used to plot individual prediction and compare with observed data and population prediction for each individual separately

plot_pmx.eta_pairs

Plot random effect correlation plot

get_conts

Get continuous covariates

is.pmx_gpar

Check if an object is a pmx_gpar class

get_occ

Get controller occasional covariates

plot_names

Get plot names

pmx_bloq

Creates BLOQ object attributes

input_finegrid

Merge input and fingrid data sets

pk_occ

Creates pmx controller using monlix data having Occasional variable

pk_pd

Creates pkpd pmx controller using package internal data

get_covariates

Get covariates variables

get_cats

Get category covariates

plot_pmx

This is a generic plot method that produces all plots by default described in pmx model evaluation guidance.

get_strats

Get extra stratification variables

pmx_comp_shrink

Compute Shrinkage

pmx_gpar

Handling pmx Graphical parameters

pmx_theme

Define ggPMX theme

print.configs

This function can be used to print configuration of the defined object using S3 method.

print.pmxClass

Print pmxClass object

pmx_get_configs

Get List of built-in configurations

pmx_sim

Create simulation object

l_left_join

Merge 2 lists

ggPMX

ggPMX: A ggplot2 toolbox for Nonlinear Mixed-Effect Model graphical

pmx

Create a pmx object

load_config

Obtain the data source config

pmxOptions

This function can be used to set ggPMX options

Individual plot

Eta matrix plot

This function plot EBE versus covariates using qq plots

load_data_set

Load data set

pmx_plot

Generic pmx plot

load_source

Load all/or some source data set

plot_pmx.distrib

Plot EBE distribution

plot_pmx.residual

This function plots residual for each observed value by finding the difference between observed and predicted points. It also fits a distribution to the residual value.

plot_pmx.pmx_dens

This function plot EBE versus covariates using qq plots

plot_shrink

Plot shrink in eta matric

plots

Get plots description

pmx_endpoint

Creates pmx endpoint object

plot_pmx.pmx_gpar

The ggPMX base plot function

print.pmxConfig

S3 method print pmxConfig object

[.pmx_gpar

Method for subsetting "pmx_gpar" objects

pmx_config

This function can be used to define the pmx configuration used in plots. e.g. Monolox/Nonmem

pmx_copy

Creates a deep copy of the controller

print.pmx_gpar

Print pmx_gpar object

pmx_plot_cats

Generic pmx stratified plot

pmx_plot_iwres_dens

IWRES density plot

reexports

Objects exported from other packages

pmx_plot_vpc

VPC plot

pmx_vpc_obs

Sets vpc observation layer

residual

This function create a residual for each observed value and also generates a residual distribution

pmx_filter

filter data in a pmx controller

theophylline

Creates pmx controller using theophylline data

pmx_vpc_bin

Creates vpc bins

set_abbrev

update or add a new abbreviation

pmx_report

Generates ggpmX report from a pre-defined template

pmx_vpc_ci

Sets vpc confidence interval layer

residual_scatter

Scatter residual plots

pmx_report_template

Gets build-in report templates

pmx_update

Update plot object

pmx_settings

Create controller global settings

pmx_vpc

Creates vpc object

read_input

Read Modelling input data

pmx_dens

Creates a density plot object

pmx_cov

Select/Map covariates using human labels

plot_pmx.eta_cov

This plots an ETA covariance matrix which can be used to define the co-relation between the parameters and its shrinkage

print.abbreviation

S3 print abbreviation

pmx_qq_plot

Quantile-quantile plots

pmx_vpc_rug

Sets vpc rug layer

pmx_qq

This function creates a qq plot object

read_mlx_par_est

Read MONOLIX parameter estimation file

pmx_vpc_pi

Sets vpc percentile layer

read_mlx_ind_est

Read MONOLIX individual parameters

set_data

Set a controller data set

set_plot

Create a new plot of the desired type

read_mlx_pred

Read MONOLIX model predictions

wrap_formula

merge facets formula with new formula

No Results!

Name
ggPMX-guide.Rmd
ggPMX_arch.png
No Results!

Name

ggPMX-guide.Rmd

ggPMX_arch.png