Nothing
csmTemp2sidedDelta <-
function(data, moreExtremeMat, Ns, int, alternative, lookupArray, doublePvalue, delta, reject.alpha, checkPrev, prevMoreExtremeMat){
# Only use z-pooled for ties
TX <- zpooled_TX(NULL, Ns, delta)
TX[, 3] <- signif(TX[ , 3], 12) #Remove rounding errors
TX <- TX[order(TX[,1], TX[,2]), ]
TX[,3] <- -abs(TX[,3])
nIter <- 1
# Use a while loop (instead of recursive loop) to prevent error: "node stack overflow; no more error handlers available" #
while (TRUE) {
AC <- which(moreExtremeMat==0, arr.ind = TRUE) - 1
AC <- cbind(AC, (AC[,1]/Ns[1] - AC[,2]/Ns[2]) < delta)
AC_LT <- AC[AC[,3] == 0, 1:2, drop=FALSE]
AC_LT <- AC_LT[order(AC_LT[,1],AC_LT[,2]), , drop=FALSE]
AC_LT <- AC_LT[!duplicated(AC_LT[,1]), , drop=FALSE]
AC_LT <- AC_LT[order(AC_LT[,2],-AC_LT[,1]), , drop=FALSE]
AC_LT <- AC_LT[!duplicated(AC_LT[,2]), , drop=FALSE]
AC_UT <- AC[AC[,3] == 1, 1:2, drop=FALSE]
AC_UT <- AC_UT[order(AC_UT[,1],-AC_UT[,2]), , drop=FALSE]
AC_UT <- AC_UT[!duplicated(AC_UT[,1]), , drop=FALSE]
AC_UT <- AC_UT[order(AC_UT[,2],AC_UT[,1]), , drop=FALSE]
AC_UT <- AC_UT[!duplicated(AC_UT[,2]), , drop=FALSE]
AC <- rbind(AC_LT, AC_UT)
#Calculate the possible more extreme test statistic:
Tbls <- which(moreExtremeMat==1, arr.ind = TRUE) - 1
CcondAC <- rep(0, nrow(AC))
for (j in 1:nrow(AC)) {
CcondAC[j] <- maxPvalueLookup(rbind(Tbls, AC[j,]),
int=int, lookupArray=lookupArray, doublePvalue=doublePvalue)$pvalue
}
smallestPvalue <- min(round(CcondAC, digits=12))
if (!is.null(reject.alpha) && smallestPvalue > reject.alpha) {
# If looking at a specific dataset, then just return FALSE; otherwise, trying to form rejection region
if (!is.null(data)) { return(FALSE) }
# There are 2 cases where moreExtremeMat may be incorrect and needs to be updated:
# (1) if no tables have been added and even most extreme table is not significant (unlikely)
# (2) if previously added two tables where individually the p-values are < alpha, but together are larger than alpha (possible)
if (checkPrev && maxPvalueLookup(Tbls, int=int, lookupArray=lookupArray, doublePvalue=doublePvalue)$pvalue > reject.alpha) {
moreExtremeMat <- prevMoreExtremeMat
}
return(moreExtremeMat)
}
# Update moreExtremeMat
addRow <- AC[which(round(CcondAC, digits=12) == smallestPvalue), , drop=FALSE] + 1
# If there are ties, use Z-test to break ties
if (nrow(addRow) > 1) {
TXties <- cbind(addRow, apply(addRow, 1, function(x) { TX[TX[ , 1] == (x[1]-1) & TX[ , 2] == (x[2]-1), 3] }))
TXties <- TXties[order(TXties[,3]), ]
addRow <- TXties[TXties[ , 3] <= TXties[1,3], 1:2, drop=FALSE]
}
checkPrev <- (nrow(addRow) > 1)
prevMoreExtremeMat <- moreExtremeMat
for (j in 1:nrow(addRow)) {
moreExtremeMat[addRow[j,1], addRow[j,2]] <- 1
#if (alternative == 'two.sided') { moreExtremeMat[Ns[1] + 2 - addRow[j,1], Ns[2] + 2 - addRow[j,2]] <- 1 }
if (addRow[j,2] >= 2 && is.na(moreExtremeMat[addRow[j,1], addRow[j,2]-1])) { moreExtremeMat[addRow[j,1], addRow[j,2]-1] <- 0 }
if (addRow[j,1] <= Ns[1] && is.na(moreExtremeMat[addRow[j,1]+1, addRow[j,2]])) { moreExtremeMat[addRow[j,1]+1, addRow[j,2]] <- 0 }
if (addRow[j,2] <= Ns[2] && is.na(moreExtremeMat[addRow[j,1], addRow[j,2]+1])) { moreExtremeMat[addRow[j,1], addRow[j,2]+1] <- 0 }
if (addRow[j,1] >= 2 && is.na(moreExtremeMat[addRow[j,1]-1, addRow[j,2]])) { moreExtremeMat[addRow[j,1]-1, addRow[j,2]] <- 0 }
}
if (!is.null(data)) {
for (j in 1:nrow(addRow)) {
if (all(addRow[j, ]-1 == data[1,])) {
return(moreExtremeMat)
}
}
}
nIter <- nIter + 1
if (nIter %% 5000 == 0) {
print(paste0("CSM added ", nIter, " more extreme tables so far; may be too computationally intensive and suggest aborting"))
}
}
#Perform recursive loop
#csmTemp2sidedDelta(data, moreExtremeMat, Ns, int, alternative, lookupArray, doublePvalue, delta, reject.alpha, checkPrev, prevMoreExtremeMat)
}
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