Bioequivalence and Bioavailability Forum

❝ Many thanks Detlew!

❝ ❝ This is also the case for your calculations with theta0=0.9, but not so pronounced seen as with theta0=0.85. Check it by power calculations with n=120 for theta0=0.85 or theta0=0.9 and n=32. You will find the minimum (implying max. sample size) below CV=30% in both cases.

❝

❝ Confused by this part.

library(PowerTOST)
GMR <- seq(0.82, 0.95, 0.005)
CV  <- seq(0.25, 0.35, 0.005)
n   <- matrix(nrow=length(CV), ncol=length(GMR), byrow=TRUE,
              dimnames=list(CV, GMR))
pwr <- n
for (j in seq_along(CV)) {
  for (k in seq_along(GMR)) {
    x <- sampleN.RSABE(CV=CV[j], theta0=GMR[k],
                       design="2x2x4", print=FALSE,
                       details=FALSE)
    if (is.na(x[["Sample size"]])) { # 2nd try if necessary
      x <- sampleN.RSABE(CV=CV[j], theta0=GMR[k],
                         design="2x2x4", print=FALSE,
                         details=FALSE, nstart=x[["nlast"]])
    }
    n[j, k]   <- x[["Sample size"]]
    pwr[j, k] <- x[["Achieved power"]]
  }
}
print(n)
print(pwr)
max.n   <- apply(n, 2, max)     # maximum n for each GMR
min.pwr <- vector()             # explore min. power
for (k in seq_along(GMR)) {
  x <- n[, k]
  y <- which(x == max.n[k]) # max. sample size(s)
  if (length(y) == 1) { # already there
    min.pwr[k] <- names(y)
  } else {              # pick the minimum
    min.pwr[k] <- names(which(pwr[y, k] == min(pwr[y, k])))
  }
}
min.pwr <- as.numeric(min.pwr)
shift   <- diff(range(GMR))*0.01
plot(GMR, min.pwr, type="p", ylim=range(CV),
  ylab="CV for maximum n", las=1)
abline(h=0.3, lty=3)
text(GMR-shift, min.pwr, labels=max.n,
  cex=0.9, srt=90, pos=1, offset=1.6)