Nothing
findN1N2R1R2twoarm <- function(nmin, nmax, e1=FALSE){
nposs <- nmin:nmax
n1.list <- list()
n2.list <- list()
for(i in 1:length(nposs)){
n1.list[[i]] <- 1:(nposs[i]-1)
n2.list[[i]] <- nposs[i]-n1.list[[i]]
}
# All possibilities together:
n1 <- rev(unlist(n1.list))
n2 <- rev(unlist(n2.list))
n <- n1 + n2
ns <- cbind(n1, n2, n)
################################ FIND COMBNS OF R1 AND R ###############################
r1.list <- vector("list")
ns.list <- vector("list")
for(i in 1:nrow(ns)){
r1.list[[i]] <- -n1[i]:n1[i] # r1 values: -n1 to n1, for each possible n1
#ns.list[[i]] <-
}
rownames(ns) <- 1:nrow(ns)
ns <- ns[rep(row.names(ns), sapply(r1.list, length)), ] # duplicate each row so that there are sufficient rows for each r1 value
ns <- cbind(ns, unlist(r1.list))
colnames(ns)[4] <- "r1"
######### Add possible r values:
r.list1 <- apply(ns, 1, function(x) {(x["r1"]-x["n2"]):x["n"]}) # r must satisfy r > r1 and r < n. Also, number of responses required in stage 2 (r2-r1) must be at most n2
how.many.rs <- sapply(r.list1, length)
row.names(ns) <- 1:nrow(ns)
ns <- ns[rep(row.names(ns), how.many.rs), ] # duplicate each row a certain number of times
ns <- cbind(ns, unlist(r.list1))
colnames(ns)[5] <- "r2"
### Finally, add e1 for stopping for benefit:
if(e1==TRUE)
{
} else {
rownames(ns) <- 1:nrow(ns)
ns <- data.frame(ns)
}
return(ns)
}
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