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#
# This was compared to JAFROC Version 4.2.1 (run using Windows-8 under VMware Fusion on iMac)
# Results are in inst/JAFROC
# It checks out with Windows JAFROC for dataset02 and DfFroc2Roc(dataset04), i.e., VanDyke and FedRoc datasets
# Current Iowa software does not do DBM analysis;
# The outputs were also compared to current
# Iowa software and agrees for all except minor differences for FRRC (since in OR analysis the ddf is Inf instead
# of (I-1)(K-1))
#
DBMSummaryRRFC <- function(dataset, FOMs, ANOVA, alpha, diffTRName) {
readerID <- dataset$descriptions$readerID
modalityID <- dataset$descriptions$modalityID
I <- length(modalityID)
J <- length(readerID)
K <- dim(dataset$ratings$NL)[3]
trtMeans <- FOMs$trtMeans
trtMeanDiffs <- FOMs$trtMeanDiffs$Estimate
TRCanova <- ANOVA$TRCanova
msDen <- TRCanova["TR", "MS"]
f <- TRCanova["T", "MS"]/msDen
ddf <- (I - 1) * (J - 1)
p <- 1 - pf(f, I - 1, ddf)
RRFC <- list()
RRFC$FTests <- data.frame(DF = c((I-1),ddf),
MS = c(TRCanova["T", "MS"], msDen),
FStat = c(f,NA),
p = c(p,NA),
row.names = c("Treatment", "Error"),
stringsAsFactors = FALSE)
stdErr <- sqrt(2 * msDen/J/K)
tStat <- vector()
PrGTt <- vector()
CI <- array(dim = c(choose(I,2),2))
for (i in 1:length(trtMeanDiffs)) {
tStat[i] <- trtMeanDiffs[i]/stdErr
PrGTt[i] <- 2 * pt(abs(tStat[i]), ddf, lower.tail = FALSE) # critical correction, noted by user Lucy D'Agostino McGowan
CI[i, ] <- sort(c(trtMeanDiffs[i] - qt(alpha/2, ddf) * stdErr,
trtMeanDiffs[i] + qt(alpha/2, ddf) * stdErr))
}
RRFC$ciDiffTrt <- data.frame(Estimate = trtMeanDiffs,
StdErr = rep(stdErr, choose(I, 2)),
DF = rep(ddf, choose(I, 2)),
t = tStat,
PrGTt = PrGTt,
CILower = CI[,1],
CIUpper = CI[,2],
row.names = diffTRName,
stringsAsFactors = FALSE)
dfSingle <- array(dim = I)
msDenSingle <- array(dim = I)
stdErrSingle <- array(dim = I)
CISingle <- array(dim = c(I, 2))
for (i in 1:I) {
msDenSingle[i] <- ANOVA$IndividualTrt["msR",i+1]
dfSingle[i] <- (J - 1)
stdErrSingle[i] <- sqrt(msDenSingle[i]/J/K)
CISingle[i, ] <- sort(c(trtMeans[i, "Estimate"] - qt(alpha/2, dfSingle[i]) * stdErrSingle[i],
trtMeans[i, "Estimate"] + qt(alpha/2, dfSingle[i]) * stdErrSingle[i]))
}
RRFC$ciAvgRdrEachTrt <- data.frame(Estimate = trtMeans,
StdErr = as.vector(stdErrSingle),
DF = as.vector(dfSingle),
CILower = CISingle[,1],
CIUpper = CISingle[,2],
row.names = paste0("trt", modalityID),
stringsAsFactors = FALSE)
return(RRFC)
}
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