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

Description Usage Format Methods References See Also Examples

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.

Usage

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# design <- ASSISTDesignB$new(trialParameters, designParameters, discreteData)

Format

An R6Class generator object

Methods

ASSISTDesignB$new(designParameters, trialParameters, discreteData = FALSE, boundaries)

Create a new ASSISTDesign instance object using the parameters specified. If discreteData is TRUE use a discrete distribution for the Rankin scores and designParameters must contain the appropriate distributions to sample from. If boundaries is specified, it is used

getDesignParameters,getTrialParameters, getBoundaries

Accessor methods for (obvious) object slots

setBoundaries

Modifier method for boundaries a named vector of double values with names btilde, b, and c, in that order

print()

Print the object in a human readable form

computeCriticalValues()

Compute the critical boundary value c_α

explore(numberOfSimulations = 5000, rngSeed = 12345)

Explore the design using the specified number of simulations and random number seed. There are further parameters. By default trueParameters = self$getDesignParameters() as would be the case for a Type I error calculation. If changed, would yield power. Also showProgress = TRUE/FALSE, saveRawData = TRUE/FALSE control raw data saves and display of progress. Returns a list of results

analyze(trialExploration)

Analyze the design given the trialExploration which is the result of a call to explore to simulate the design. Return a list of summary quantities

summary(analysis)

Print the operating characteristics of the design, using the analysis result from the analyze call

References

Adaptive Choice of Patient Subgroup for Comparing Two Treatments by Tze Leung Lai and Philip W. Lavori and Olivia Yueh-Wen Liao. Contemporary Clinical Trials, Vol. 39, No. 2, pp 191-200 (2014). doi:10.1016/j.cct.2014.09.001g

See Also

ASSISTDesign which is a superclass of this object

Examples

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## 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 May 6, 2019, 1:02 a.m.