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getExpectation

Get expectations of a randomization list

Description

Generates a matrix of the expectations of the included patients in the clinical trial.

Usage

getExpectation(randSeq, issue, endp)

## S4 method for signature 'randSeq,missing,expEndp'
getExpectation(randSeq, endp)

## S4 method for signature 'randSeq,missing,normEndp'
getExpectation(randSeq, endp)

## S4 method for signature 'randSeq,power,normEndp'
getExpectation(randSeq, issue, endp)

## S4 method for signature 'randSeq,chronBias,normEndp'
getExpectation(randSeq, issue, endp)

## S4 method for signature 'randSeq,chronBias,expEndp'
getExpectation(randSeq, issue, endp)

## S4 method for signature 'randSeq,chronBias,missing'
getExpectation(randSeq, issue)

## S4 method for signature 'randSeq,selBias,normEndp'
getExpectation(randSeq, issue, endp)

## S4 method for signature 'randSeq,selBias,expEndp'
getExpectation(randSeq, issue, endp)

## S4 method for signature 'randSeq,selBias,missing'
getExpectation(randSeq, issue)

## S4 method for signature 'randSeq,combinedBias,normEndp'
getExpectation(randSeq, issue, endp)

## S4 method for signature 'randSeq,combinedBias,expEndp'
getExpectation(randSeq, issue, endp)

## S4 method for signature 'randSeq,combinedBiasStepTrend,normEndp'
getExpectation(randSeq, issue, endp)

## S4 method for signature 'randSeq,combinedBiasStepTrend,expEndp'
getExpectation(randSeq, issue, endp)

Arguments

randSeq

object of the class randSeq.
issue

object of the class issue (optional).
endp

object of the class endpoint (optional).

Details

It is assumed that the expectations of the included patients in a clinical trial can be influenced in three different ways:

  • The strength of selection bias and the guessing strategy of the investigator (see selBias).

  • The strength of a linear time trend, which is described by an object of the class chronBias.

  • The expectations of the investigated treatment groups can be different (see e.g. normEndp).

Examples

# get Expectation for a normal endpoint
myPar <- bsdPar(10, 2)
M <- genSeq(myPar, 2)
cs <- selBias("CS", 2, "sim")
endp <- normEndp(mu = c(2, 2), sigma = c(1, 1))
getExpectation(M, cs, endp)

# get Expectation for an exponential endpoint
cs <- selBias("CS", 0.1 , "sim")
endp <- expEndp(lambda = c(0.5, 1), cenTime = 10, cenRate = 0.01)
getExpectation(M, cs, endp)
randomizeR

Randomization for Clinical Trials

v2.0.0
GPL (>= 3)
Authors
David Schindler [aut], Diane Uschner [aut, cre], Marcia Viviane Rueckbeil [ctb], Martin Manolov [ctb], Thi Mui Pham [ctb], Michael Martini [ctb], Ralf-Dieter Hilgers [aut, ths], Nicole Heussen [aut, ths]
Initial release
2019-11-15

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