computeResponseSummary: Given interim data, compute the response end-point summary

In sp23design: Design and Simulation of Seamless Phase II-III Clinical Trials

Given interim data, compute the response end-point summary

Description

Compute the response end-point summary for interim data. This will include the proportion of responses, the proportion of people on treatment and control etc.

Usage

computeResponseSummary(interimData)

Arguments

interimData

The interim data for the clinical trial

Details

The result is a vector of counts and proportions

Value

m0	number on control arm
m1	number on treatment arm
y0	number of responses in control
y1	number of responses in treatment
numberOfTotalResponses	number of total responses in both arms
controlRespProp	the proportion of responders in control arm
treatmentRespProp	the proportion of responders in the treatment arm
pooledProp	the pooled response proportion

Author(s)

Mei-Chiung Shih, Balasubramanian Narasimhan, Pei He

References

Lai, Tze Leung and Lavori, Philip W. and Shih, Mei-Chiung. Sequential Design of Phase II-III Cancer Trials, Statistics in Medicine, Volume 31, issue 18, p.1944-1960, 2012.

Examples

## Not run: 
  trialParameters <- list(minimumNumberOfEvents = 20,
                              minimumIncreaseInV = 0.2,
                              numberRecruitedEachYear = c(80, 120, 160, 160),
                              followupTime = 3,
                              adminCensoringTime = 7,
                              interimLookTime = c(1, 2, 3, 5, 7),
                              type1ErrorForResponse = 0.05,
                              type2ErrorForResponse = 0.01,
                              glrBoundarySidedness = "one", # one sided or two-sided
                              type1Error = 0.05,
                              type2Error = 0.10,
                              epsType1 = 1/3,
                              epsType2 = 1/3)

  trueParameters <- list(p0 = 0.3,
                             p1 = 0.3,
                             pdiffHyp=0.3,
                             theta = list(
                                     alpha = 0,
                                     beta = 0,
                                     gamma = 0),
                             baselineLambda = 0.35,
                             etaHyp = 0.25)
  rngSeed <- 9872831

  d <- generateClinicalTrialData(nRec = trialParameters$numberRecruitedEachYear,
                                     nFUp = trialParameters$followupTime,
                                     pi0 = trueParameters$p0,
                                     pi1 = trueParameters$p1,
                                     theta = trueParameters$theta,
                                     lambda0 = trueParameters$baselineLambda)
  dInterim <- generateInterimData(d, trialParameters$interimLookTime[2],
                                      trialParameters$adminCensoringTime)
  computeResponseSummary(dInterim)

## End(Not run)

sp23design documentation built on April 19, 2022, 5:08 p.m.