Generate and Report Model Diagnostics from NLME or NONMEM runs

Shiny application to generate, customize, and report diagnostic plots and tables from NLME or NONMEM output files. Create an Rmarkdown file of tagged model diagnostics and render into submission ready report.

resultsUI(model, xpdb = NULL, tagged = NULL, settings = NULL, ...)

Arguments

model

A single object, vector, or list of objects of class NlmePmlModel.

xpdb

A single object or list of objects of class xpose_data.

tagged

List of tagged objects returned from previous tagged <- resultsUI() session.

settings

List of settings (e.g., settings.Rds) returned from previous Shiny session.

...

Additional arguments for Pirana integration.

Examples

if (FALSE) {


# RsNLME
library(Certara.RsNLME)
library(Certara.ModelResults)

model1 <- pkmodel(numCompartments = 1,
                 data = pkData,
                 ID = "Subject",
                 Time = "Act_Time",
                 A1 = "Amount",
                 CObs = "Conc",
                 modelName = "OneCpt_IVBolus_FOCE-ELS")

baseFitJob1 <- fitmodel(model1)


model2 <- pkmodel(numCompartments = 2,
                 data = pkData,
                 ID = "Subject",
                 Time = "Act_Time",
                 A1 = "Amount",
                 CObs = "Conc",
                 modelName = "TwCpt_IVBolus_FOCE-ELS")

baseFitJob2 <- fitmodel(model2)

# Run Model Results
resultsUI(model = c(model1, model2))


# NONMEM via xpose

library(Certara.ModelResults)
library(xpose)

xpdb <- xpose_data(
  runno = "1",
  prefix = "run",
  ext = ".lst",
  dir = "./NONMEM/Hands_onB/")

results(xpdb = xpdb)

# Multiple models

xpdb_multiple <- list(
 run1 = xpose_data(file = "run1.lst"),
 run2 = xpose_data(file = "run2.lst"),
 run3 = xpose_data(file = "run3.lst"),
 run4 = xpose_data(file = "run4.lst")
)
}