inst/shiny/text/howto.md

In coveffectsplot: Produce Forest Plots to Visualize Covariate Effects

1. Upload your data file in csv format. R default options for read.csv will apply except for missing values where both (NA) and dot (.) are treated as missing. read.csv("yourdata.csv", na.strings = c("NA", "."))

2. The uploaded data will map automatically it is a must that you have the following column names:

   • paramname: Parameter on which the effects are shown e.g. CL, Cmax, AUC etc.
   • covname: Covariate name that the effects belong to e.g. Weight, SEX, Dose etc.
   • label: Covariate value that the effects of which is shown e.g. 50 kg, 50 kg\90 kg (here the reference value is contained in the label). mid: Middle value for the effects usually the median from the uncertainty distribution.
   • lower: Lower value for the effects usually the 2.5% or 5% from the uncertainty distribution.
   • upper: Upper value for the effects usually the 97.5% or 95% from the uncertainty distribution.

Refer to the repo readme file for additional info: Click Here to go to the github repo.

The package vignettes include and introduction and multiple detailed examples: Introduction to coveffectsplot. PK example PK PD example Exposure Response

Contact me @ [e-mail] for feedback/bugs/features/pull requests!

Samer Mouksassi 2020

coveffectsplot documentation built on Sept. 18, 2023, 5:06 p.m.