powerDTR {smartDesign}

Power Dynamic Treatment Regimen (DTR) Trial design clinical trial calculations

Description

Power Calculations Comparing two Dynamic Treatment Regimen (DTR) Trial design clinical trial calculations

Usage

powerDTR(dtr1, dtr2, pG_A1 = 0.8, pG_A2 = 0.8, alpha=0.05)

Arguments

dtr1

an object of smartDTR class, created by function of the same name

dtr2

an object of smartDTR class, created by function of the same name

pG_A1

probability of response to therapy given assignment to A1

pG_A2

probability of response to therapy given assignment to A2

alpha

accepted type-I error rate for power calculations

Details

more details on power DTR

Value

An object of the powerDTR S3 class, with the following elements:

powerdat:

data.frame with sens, spec, mu, sigsq and sample size, power

Author(s)

Jun (Jessie) He, Aberaham Eyman-Casey, Jason P. Sinnwell, Mayo Clinic

Examples

  mumat13 <- cbind(G1=c(30,35), G0=c(20,28))
  varmat13 <- cbind(G1=c(100,100),G0=c(100,100))

  dtr13 <- smartDTR(mu_Barm=mumat13, sigsq_Barm=varmat13,
                   Barm=c(1,3), nsubject=252, pG_A1=0.8)

  mumat24 <- cbind(G1=c(25,32), G0=c(18,23))
  varmat24 <- cbind(G1=c(100,100),G0=c(100,100))

  dtr24 <- smartDTR(mu_Barm=mumat24, sigsq_Barm=varmat24,
                   Barm=c(2,4), nsubject=252, pG_A1=0.8, pG_A2=0.8)

  pdtr13vs24 <- powerDTR(dtr13, dtr24)
  print(pdtr13vs24)  ## plot(pdtr13vs24)