## T1E after 1st stage in TSDs [Two-Stage / GS Designs]

Hi Mittyri,

❝ could you please guide me regarding the function to be used for T1E estimation after 1st stage of Potvin methods (Power2Stage R package)?

Really in the first stage? Negligible for the combinations where you get the largest TIE overall. Anyhow, your wish is my command:

library(Power2Stage) # alpha0 = 0.05 for method = "C" and alpha = c(0.0294, 0.0294) for method = "B" # and "C" are defaults; GMR = 0.95, targetpower = 0.8, if theta0 = 0.8 or 1.25, # by default nsims = 1e6. CV  <- 0.2 n1  <- 12 # That’s an evil combination; commonly the largest # TIE with a relatively small CV and very small n1. res <- data.frame(method = c("B", "C"), alpha0 = 0.05, alpha = 0.0294,                   TIE.stage1 = NA_real_, TIE.stage2 = NA_real_) for (j in 1:nrow(res)) {   tmp         <- power.tsd(method = res$method[j], n1 = n1, CV = CV, theta0 = 1.25) res[j, 4:5] <- c(tmp$pBE_s1, tmp$pBE) } res$alpha0[1] <- "" print(res, row.names = FALSE)  method alpha0  alpha TIE.stage1 TIE.stage2       B        0.0294   0.028849   0.046273       C   0.05 0.0294   0.035777   0.051100

Belt plus suspenders:

library(PowerTOST) # I don’t recommend that but let n1 = n of a fixed sample design # i.e., high chance of passing in the first stage of a TSD. CV  <- 0.2 n1  <- sampleN.TOST(CV = CV, print = FALSE)[["Sample size"]] for (j in 1:nrow(res)) {   tmp         <- power.tsd(method = res$method[j], n1 = n1, CV = CV, theta0 = 1.25) res[j, 4:5] <- c(tmp$pBE_s1, tmp$pBE) } res$alpha0[1] <- "" print(res, row.names = FALSE)  method alpha0  alpha TIE.stage1 TIE.stage2       B        0.0294   0.029142   0.034816       C   0.05 0.0294   0.045318   0.049042

PS: I changed the category from . Though you asked for the -package Power2Stage, perhaps somebody would have the balls to roll out own code.

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