generateClinicalTrialData function

A function to generate some clinical trial data according the joint model of response and survival for simulations

A function to generate some clinical trial data according the joint model of response and survival for simulations

The data is generated according to the model specified in the reference below, specifically, [REMOVE_ME]λ(tY,Z)=λ0(t)exp(αY+βZ+γYZ)[REMOVEME2] \lambda(t \mid Y,Z)=\lambda_0(t) \exp(\alpha Y + \beta Z + \gamma YZ) [REMOVE_ME_2]

Description

The data is generated according to the model specified in the reference below, specifically,

λ(tY,Z)=λ0(t)exp(αY+βZ+γYZ) \lambda(t \mid Y,Z)=\lambda_0(t) \exp(\alpha Y + \beta Z + \gamma YZ)
generateClinicalTrialData(nRec, nFUp, pi0, pi1, theta, lambda0, blockSize = 10)

Arguments

  • nRec: the number of patients recruited every year. Length(nRec) is the number of years of recruitment
  • nFUp: the number of additional years of followup
  • pi0: the probability of response under control arm
  • pi1: the probability of response under treatment arm
  • theta: the three dimensional parameter (α,β,γ)(\alpha, \beta, \gamma) of the joint response/survival model
  • lambda0: the baseline hazard rate
  • blockSize: the size of the blocks for randomization of the treatment/control; we use block randomization

Details

Generates data from an exponentail distribution according to the model and adhering to the recruitment goals for each calendar year

Returns

A data frame consisting of the following variables. - entryTime: entry time of the patient into the trial

  • responseIndicator: an indicator of patient being a responder or not

  • treatmentIndicator: an indicator of patient being in treatment arm or control

  • timeToEvent: the time to event or death in the language of the paper

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.

Author(s)

Mei-Chiung Shih, Balasubramanian Narasimhan, Pei He

Examples

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)
  • Maintainer: Balasubramanian Narasimhan
  • License: LGPL-3
  • Last published: 2022-04-19

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