smartDesign (version 0.74)

powerDTR: 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)

Value

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

powerdat:

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

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

Author

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

Details

more details on power DTR

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)