ASSISTDesignB: A fixed sample design to compare against the adaptive...

In ASSISTant: Adaptive Subgroup Selection in Group Sequential Trials

A fixed sample design to compare against the adaptive clinical trial design

Description

ASSISTDesignB objects are used to design a trial with certain characteristics provided in the object instantiation method. This design differs from ASSISTDesign in only how it computes the critical boundaries, how it performs the interim look, and what quantities are computed in a trial run.

Super class

ASSISTant::ASSISTDesign -> ASSISTDesignB

Methods

Public methods

• ASSISTDesignB$computeCriticalValues()

• ASSISTDesignB$explore()

• ASSISTDesignB$analyze()

• ASSISTDesignB$summary()

• ASSISTDesignB$clone()

Inherited methods

• ASSISTant::ASSISTDesign$getBoundaries()
• ASSISTant::ASSISTDesign$getDesignParameters()
• ASSISTant::ASSISTDesign$getTrialParameters()
• ASSISTant::ASSISTDesign$initialize()
• ASSISTant::ASSISTDesign$performInterimLook()
• ASSISTant::ASSISTDesign$print()
• ASSISTant::ASSISTDesign$setBoundaries()

---

Method computeCriticalValues()

Compute the critical boundary value c_α

Usage

ASSISTDesignB$computeCriticalValues()

Returns

a named vector of a single value containing the value for c

---

Method explore()

Explore the design using the specified number of simulations, random number seed, and further parameters.

Usage

ASSISTDesignB$explore(
  numberOfSimulations = 100,
  rngSeed = 12345,
  trueParameters = self$getDesignParameters(),
  showProgress = TRUE,
  saveRawData = FALSE
)

Arguments

numberOfSimulations

default number of simulations is 100

rngSeed

default seed is 12345

trueParameters

the state of nature, by default the value of self$getDesignParameters() as would be the case for a Type I error calculation. If changed, would yield power.

showProgress

a boolean flag to show progress, default TRUE

saveRawData

a flag (default FALSE) to indicate if raw data has to be saved

Returns

a list of results

---

Method analyze()

Analyze the exploration data from trial

Usage

ASSISTDesignB$analyze(trialExploration)

Arguments

trialExploration

the result of a call to explore() to simulate the design

Returns

Return a list of summary quantities

---

Method summary()

Print the operating characteristics of the design using the analysis data

Usage

ASSISTDesignB$summary(analysis)

Arguments

analysis

the analysis result from the analyze() call

---

Method clone()

The objects of this class are cloneable with this method.

Usage

ASSISTDesignB$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

ASSISTDesign which is a superclass of this object

Examples

## Not run: 
data(LLL.SETTINGS)
prevalence <- LLL.SETTINGS$prevalences$table1
scenario <- LLL.SETTINGS$scenarios$S0
designParameters <- list(prevalence = prevalence,
                       mean = scenario$mean,
                       sd = scenario$sd)
designB <- ASSISTDesignB$new(trialParameters = LLL.SETTINGS$trialParameters,
                            designParameters = designParameters)
print(designB)
## A realistic design uses 5000 simulations or more!
result <- designB$explore(showProgress = interactive())
analysis <- designB$analyze(result)
designB$summary(analysis)

## End(Not run)
## For full examples, try:
## browseURL(system.file("full_doc/ASSISTant.html", package="ASSISTant"))

ASSISTant documentation built on Dec. 2, 2022, 5:12 p.m.