Plot of the DLE and efficacy curve side by side given a DLE pseudo model, a DLE sample, an efficacy pseudo model and a given efficacy sample

Plot of the DLE and efficacy curve side by side given a DLE pseudo model, a DLE sample, an efficacy pseudo model and a given efficacy sample

Plot of the dose-DLE and dose-efficacy curve side by side given a DLE pseudo model and a given pseudo efficacy model without DLE and efficacy samples

Usage

plotDualResponses(DLEmodel, DLEsamples, Effmodel, Effsamples, data, ...)

# S4 method for class 'ModelTox,Samples,ModelEff,Samples'
plotDualResponses(
  DLEmodel,
  DLEsamples,
  Effmodel,
  Effsamples,
  data,
  extrapolate = TRUE,
  showLegend = FALSE,
  ...
)

# S4 method for class 'ModelTox,missing,ModelEff,missing'
plotDualResponses(DLEmodel, DLEsamples, Effmodel, Effsamples, data, ...)

Arguments

DLEmodel

the pseudo DLE model of ModelTox class object

DLEsamples

the DLE samples of Samples class object

Effmodel

the pseudo efficacy model of ModelEff class object

Effsamples

the Efficacy samples of Samples class object

data

the data input of DataDual class object

...

additional arguments for the parent method plot,Samples,GeneralModel-method

extrapolate

should the biomarker fit be extrapolated to the whole dose grid? (default)

showLegend

should the legend be shown? (not default)

Value

This returns the ggplot object with the dose-toxicity and dose-efficacy model fits

Functions

• plotDualResponses( DLEmodel = ModelTox, DLEsamples = Samples, Effmodel = ModelEff, Effsamples = Samples ): function still to be documented

• plotDualResponses( DLEmodel = ModelTox, DLEsamples = missing, Effmodel = ModelEff, Effsamples = missing ): Plot the DLE and efficacy curve side by side given a DLE model and an efficacy model without any samples

Examples

# nolint start

## we need a data object with doses >= 1:
data <- DataDual(
  x = c(25, 50, 25, 50, 75, 300, 250, 150),
  y = c(0, 0, 0, 0, 0, 1, 1, 0),
  w = c(0.31, 0.42, 0.59, 0.45, 0.6, 0.7, 0.6, 0.52),
  doseGrid = seq(25, 300, 25),
  placebo = FALSE
)
#> Used default patient IDs!
#> Used best guess cohort indices!
##plot the dose-DLE and dose-efficacy curves in two plots with DLE and efficacy samples
##define the DLE model which must be of 'ModelTox' class
##(e.g 'LogisticIndepBeta' class model)
DLEmodel <- LogisticIndepBeta(
  binDLE = c(1.05, 1.8),
  DLEweights = c(3, 3),
  DLEdose = c(25, 300),
  data = data
)
## define the efficacy model which must be of 'ModelEff' class
## (e.g 'Effloglog' class)
Effmodel <- Effloglog(
  eff = c(1.223, 2.513),
  eff_dose = c(25, 300),
  nu = c(a = 1, b = 0.025),
  data = data
)
##define the DLE sample of 'Samples' class
##set up the same data set in class 'Data' for MCMC sampling for DLE
data1 <- Data(x = data@x, y = data@y, doseGrid = data@doseGrid)
#> Used default patient IDs!
#> Used best guess cohort indices!
##Specify the options for MCMC
options <- McmcOptions(burnin = 100, step = 2, samples = 1000)


DLEsamples <- mcmc(data = data1, model = DLEmodel, options = options)
##define the efficacy sample of 'Samples' class
Effsamples <- mcmc(data = data, model = Effmodel, options = options)
##plot the dose-DLE and dose-efficacy curves with two plot side by side.
##For each curve the 95% credibility interval of the two samples are alos given
plotDualResponses(
  DLEmodel = DLEmodel,
  DLEsamples = DLEsamples,
  Effmodel = Effmodel,
  Effsamples = Effsamples,
  data = data
)

# nolint end
# nolint start

## we need a data object with doses >= 1:
data <- DataDual(
  x = c(25, 50, 25, 50, 75, 300, 250, 150),
  y = c(0, 0, 0, 0, 0, 1, 1, 0),
  w = c(0.31, 0.42, 0.59, 0.45, 0.6, 0.7, 0.6, 0.52),
  doseGrid = seq(25, 300, 25),
  placebo = FALSE
)
#> Used default patient IDs!
#> Used best guess cohort indices!
##plot the dose-DLE and dose-efficacy curves in two plots without DLE and efficacy samples
##define the DLE model which must be of 'ModelTox' class
##(e.g 'LogisticIndepBeta' class model)
DLEmodel <- LogisticIndepBeta(
  binDLE = c(1.05, 1.8),
  DLEweights = c(3, 3),
  DLEdose = c(25, 300),
  data = data
)
## define the efficacy model which must be of 'ModelEff' class
## (e.g 'Effloglog' class)
Effmodel <- Effloglog(
  eff = c(1.223, 2.513),
  eff_dose = c(25, 300),
  nu = c(a = 1, b = 0.025),
  data = data
)
##plot the dose-DLE and dose-efficacy curves with two plot side by side.
plotDualResponses(DLEmodel = DLEmodel, Effmodel = Effmodel, data = data)
#> Warning: Arguments in `...` must be used.
#> ✖ Problematic argument:
#> • group = group
#> ℹ Did you misspell an argument name?
#> Warning: Arguments in `...` must be used.
#> ✖ Problematic argument:
#> • group = group
#> ℹ Did you misspell an argument name?


# nolint end