Two-stage design ❎ RSABE [Design Issues]

posted by Helmut Homepage – Vienna, Austria, 2021-05-14 20:14 (135 d 10:29 ago) – Posting: # 22355
Views: 816

Hi Achievwin,

sorry. See there.

If you are – very – courageous, you can opt for Bonferroni (α = 0.025). All methods I know (for 2×2×2 crossover and parallel designs) require less adjustments, i.e., a higher α. No idea whether that’s acceptable. Ask the OGD.

library(PowerTOST)
theta0 <- 0.90
target <- 0.80
design <- "2x2x4"
CV     <- seq(0.3, 0.8, 0.025)
res    <- data.frame(CV = sprintf("%.1f%%", 100*CV))
for (j in 1:nrow(res)) {
  # sample size for α = 0.05
  res$n1[j]  <- sampleN.RSABE(alpha = 0.05, CV = CV[j],
                              theta0 = theta0, targetpower = target,
                              design = design, details = FALSE,
                              print = FALSE)[["Sample size"]]
  # sample size for α = 0.025
  res$n2[j] <- sampleN.RSABE(alpha = 0.025, CV = CV[j],
                             theta0 = theta0, targetpower = target,
                             design = design, details = FALSE,
                             print = FALSE)[["Sample size"]]
}
res$penalty <- sprintf("%+.1f%%", 100*(res$n2-res$n1)/res$n1)
names(res)[2:3] <- c("n (alpha=0.05)", "n (alpha=0.025)")
print(res, row.names = FALSE)

    CV n (alpha=0.05) n (alpha=0.025) penalty
 30.0%             32              40  +25.0%
 32.5%             30              38  +26.7%
 35.0%             28              34  +21.4%
 37.5%             26              32  +23.1%
 40.0%             24              30  +25.0%
 42.5%             24              30  +25.0%
 45.0%             24              28  +16.7%
 47.5%             22              28  +27.3%
 50.0%             22              28  +27.3%
 52.5%             22              26  +18.2%
 55.0%             22              26  +18.2%
 57.5%             22              26  +18.2%
 60.0%             24              26   +8.3%
 62.5%             24              26   +8.3%
 65.0%             24              28  +16.7%
 67.5%             24              28  +16.7%
 70.0%             26              28   +7.7%
 72.5%             26              28   +7.7%
 75.0%             26              28   +7.7%
 77.5%             28              30   +7.1%
 80.0%             28              30   +7.1%


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