Bioequivalence and Bioavailability Forum

Hi Marty,

sorry, I’m not sure whether I do understand your values.

❝ theta0 = .95, confirmed. targetpower = .8, dropout rate 10% (PowerTOST_output/0.9)

library(PowerTOST)
nadj <- function(n, do.rate, nseq = 2) { # adjusted sample size (balanced sequences)
  x  <- n / (1 - do.rate)
  return(as.integer(nseq * (x %/% nseq + as.logical(x %% nseq))))
}
CV      <- 0.18 # assumed
theta0  <- 0.95 # assumed
target  <- 0.80 # target (desired) power
do.rate <- 0.10 # anticipated dropout-rate 10%
n       <- sampleN.TOST(CV = CV, theta0 = theta0, targetpower = target,
                        design = "2x2")[["Sample size"]]

+++++++++++ Equivalence test - TOST +++++++++++
            Sample size estimation
-----------------------------------------------
Study design: 2x2 crossover
log-transformed data (multiplicative model)

alpha = 0.05, target power = 0.8
BE margins = 0.8 ... 1.25
True ratio = 0.95,  CV = 0.18

Sample size (total)
 n     power
16   0.820357

cat("adjusted sample size =", nadj(n, do.rate), "\n")

adjusted sample size = 18

❝ ❝ 2. Number of eligible subjects in the failed study (CV 0.27, PE 0.88)

❝ 27 (this is its own can of worms right?)

Given the sample size estimation above, how did you end up with 27 eligible in the study? Even if you would have targeted 90% power, we get n = 22 and nadj = 26.