contextStr <- "Compare DBM to OR for dataset02, ROC"
context(contextStr)
test_that(contextStr, {
ds <- dataset02
############################ RRRC
DBM_RRRC <- St(ds, FOM = "Wilcoxon", method = "DBM", analysisOption = "RRRC")
OR_RRRC <- St(ds, FOM = "Wilcoxon", method = "OR", analysisOption = "RRRC")
dbmfomArray <- DBM_RRRC$fomArray
orfomArray <- OR_RRRC$fomArray
for (i in 1: length(dbmfomArray)){
x <- as.numeric(dbmfomArray[[i]])
y <- as.numeric(orfomArray[[i]])
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
dbmFStatsRRRC <- as.matrix(DBM_RRRC$RRRC$FTests)[1,4] # check p values only
orFStatsRRRC <- as.matrix(OR_RRRC$RRRC$FTests)[1,4]
names(orFStatsRRRC) <- NULL
for (i in 1: length(dbmFStatsRRRC)){
x <- as.numeric(dbmFStatsRRRC[[i]])
y <- as.numeric(orFStatsRRRC[[i]])
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
dbmciDiffTrtRRRC <- as.vector(unlist(DBM_RRRC$RRRC$ciDiffTrt[,-1])) # remove 0-1 vs trt0-trt1
orciDiffTrtRRRC <- as.vector(unlist(OR_RRRC$RRRC$ciDiffTrt[,-1]))
for (i in 1: length(dbmciDiffTrtRRRC)){
x <- dbmciDiffTrtRRRC[i]
y <- orciDiffTrtRRRC[i]
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
dbmciAvgRdrEachTrtRRRC <- as.vector(unlist(DBM_RRRC$RRRC$ciAvgRdrEachTrt[,-1]))
orciAvgRdrEachTrtRRRC <- as.vector(unlist(OR_RRRC$RRRC$ciAvgRdrEachTrt[,-1]))
for (i in 1: length(dbmciAvgRdrEachTrtRRRC)){
x <- dbmciAvgRdrEachTrtRRRC[i]
y <- orciAvgRdrEachTrtRRRC[i]
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
############################ FRRC
DBM_FRRC <- St(ds, FOM = "Wilcoxon", method = "DBM", analysisOption = "FRRC")
OR_FRRC <- St(ds, FOM = "Wilcoxon", method = "OR", analysisOption = "FRRC")
dbmFStatsFRRC <- as.matrix(DBM_FRRC$FRRC$FTests)[1,4] # check p values only
orFStatsFRRC <- as.matrix(OR_FRRC$FRRC$FTests)[1,4]
names(orFStatsFRRC) <- NULL
for (i in 1: length(dbmFStatsFRRC)){
x <- as.numeric(dbmFStatsFRRC[[i]])
y <- as.numeric(orFStatsFRRC[[i]])
expect_equal(x, y, tolerance = 0.01, scale = abs(x)) # not exact match
}
dbmciDiffTrtFRRC <- as.vector(as.matrix(DBM_FRRC$FRRC$ciDiffTrt))[-c(3,4,5)]
orciDiffTrtFRRC <- as.vector(as.matrix(OR_FRRC$FRRC$ciDiffTrt))[-c(3,4)]
for (i in 1: length(dbmciDiffTrtFRRC)){
if (i == 3) next # skip infinity
x <- dbmciDiffTrtFRRC[i]
y <- orciDiffTrtFRRC[i]
expect_equal(x, y, tolerance = 0.01, scale = abs(x)) # values are not exactly equal; tolerance found by trial and error
}
dbmciAvgRdrEachTrtFRRC <- as.vector(as.matrix(DBM_FRRC$FRRC$ciAvgRdrEachTrt))
orciAvgRdrEachTrtFRRC <- as.vector(as.matrix(OR_FRRC$FRRC$ciAvgRdrEachTrt))
for (i in 1: length(dbmciAvgRdrEachTrtFRRC)){
if (i == 5) next # skip infinity
if (i == 6) next # skip infinity
x <- dbmciAvgRdrEachTrtFRRC[i]
y <- orciAvgRdrEachTrtFRRC[i]
expect_equal(x, y, tolerance = 0.001, scale = abs(x)) # values are not exactly equal
}
############################ RRFC
DBM_RRFC <- St(ds, FOM = "Wilcoxon", method = "DBM", analysisOption = "RRFC")
OR_RRFC <- St(ds, FOM = "Wilcoxon", method = "OR", analysisOption = "RRFC")
dbmFStatsRRFC <- as.matrix(DBM_RRFC$RRFC$FTests)[1,4]# check p values only
orFStatsRRFC <- as.matrix(OR_RRFC$RRFC$FTests)[1,4]
names(orFStatsRRFC) <- NULL
for (i in 1: length(dbmFStatsRRFC)){
x <- as.numeric(dbmFStatsRRFC[[i]])
y <- as.numeric(orFStatsRRFC[[i]])
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
# VarComp are not expected to be equal
dbmciDiffTrtRRFC <- as.vector(as.matrix(DBM_RRFC$RRFC$ciDiffTrt))
orciDiffTrtRRFC <- as.vector(as.matrix(OR_RRFC$RRFC$ciDiffTrt))
for (i in 1: length(dbmciDiffTrtRRFC)){
x <- dbmciDiffTrtRRFC[i]
y <- orciDiffTrtRRFC[i]
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
dbmciAvgRdrEachTrtRRFC <- as.vector(as.matrix(DBM_RRFC$RRFC$ciAvgRdrEachTrt))
orciAvgRdrEachTrtRRFC <- as.vector(as.matrix(OR_RRFC$RRFC$ciAvgRdrEachTrt))
for (i in 1: length(dbmciAvgRdrEachTrtRRFC)){
x <- dbmciAvgRdrEachTrtRRFC[i]
y <- orciAvgRdrEachTrtRRFC[i]
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
})
contextStr <- "Compare DBM to OR for dataset05, FROC, HrAuc"
context(contextStr)
test_that(contextStr, {
ds <- dataset05
DBM_RRRC <- St(ds, FOM = "HrAuc", method = "DBM", analysisOption = "RRRC")
OR_RRRC <- St(ds, FOM = "HrAuc", method = "OR", analysisOption = "RRRC")
####################################### fomArray ###########################################
dbmfomArray <- as.vector(as.matrix(DBM_RRRC$FOMs$foms))
orfomArray <- as.vector(as.matrix(OR_RRRC$FOMs$foms))
for (i in 1: length(dbmfomArray)){
x <- dbmfomArray[i]
y <- orfomArray[i]
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
####################################### FStats ###########################################
dbmFStatsRRRC <- as.vector(as.matrix(DBM_RRRC$RRRC$FTests))[-c(3,4,6,8)]
orFStatsRRRC <- as.vector(as.matrix(OR_RRRC$RRRC$FTests))[-c(3,4,6,8)]
for (i in 1: length(dbmFStatsRRRC)){
x <- as.numeric(dbmFStatsRRRC[[i]])
y <- as.numeric(orFStatsRRRC[[i]])
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
DBM_FRRC <- St(ds, FOM = "HrAuc", method = "DBM", analysisOption = "FRRC")
OR_FRRC <- St(ds, FOM = "HrAuc", method = "OR", analysisOption = "FRRC")
dbmFStatsFRRC <- DBM_FRRC$FRRC$FTests[1,4] # check p values only
orFStatsFRRC <- OR_FRRC$FRRC$FTests[1,4]
for (i in 1: length(dbmFStatsFRRC)){
x <- dbmFStatsFRRC[i]
y <- orFStatsFRRC[i]
expect_equal(x, y, tolerance = 0.01, scale = abs(x))
}
DBM_RRFC <- St(ds, FOM = "HrAuc", method = "DBM", analysisOption = "RRFC")
OR_RRFC <- St(ds, FOM = "HrAuc", method = "OR", analysisOption = "RRFC")
dbmFStatsRRFC <- DBM_RRFC$RRFC$FTests[1,4]
orFStatsRRFC <- OR_RRFC$RRFC$FTests[1,4]
for (i in 1: length(dbmFStatsRRFC)){
x <- as.numeric(dbmFStatsRRFC[[i]])
y <- as.numeric(orFStatsRRFC[[i]])
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
# VarComp are not expected to be equal
####################################### VarComp ###########################################
################################## diff and avg confidence intervals #####################
dbmciDiffTrtRRRC <- as.vector(as.matrix(DBM_RRRC$RRRC$ciDiffTrt))
orciDiffTrtRRRC <- as.vector(as.matrix(OR_RRRC$RRRC$ciDiffTrt))
for (i in 1: length(dbmciDiffTrtRRRC)){
x <- dbmciDiffTrtRRRC[i]
y <- orciDiffTrtRRRC[i]
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
dbmciAvgRdrEachTrtRRRC <- as.vector(as.matrix(DBM_RRRC$RRRC$ciAvgRdrEachTrt))
orciAvgRdrEachTrtRRRC <- as.vector(as.matrix(OR_RRRC$RRRC$ciAvgRdrEachTrt))[-(11:12)] # remove var comp
for (i in 1: length(dbmciAvgRdrEachTrtRRRC)){
x <- dbmciAvgRdrEachTrtRRRC[i]
y <- orciAvgRdrEachTrtRRRC[i]
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
dbmciDiffTrtFRRC <- as.vector(as.matrix(DBM_FRRC$FRRC$ciDiffTrt))[-3] # remove DF 0-1 vs trt0-trt1
orciDiffTrtFRRC <- as.vector(as.matrix(OR_FRRC$FRRC$ciDiffTrt))#[-1])
for (i in 1: length(dbmciDiffTrtFRRC)){
x <- dbmciDiffTrtFRRC[i]
y <- orciDiffTrtFRRC[i]
expect_equal(x, y, tolerance = 0.01, scale = abs(x)) # values are not exactly equal; tolerance found by trial and error
}
dbmciAvgRdrEachTrtFRRC <- as.vector(as.matrix(DBM_FRRC$FRRC$ciAvgRdrEachTrt))
orciAvgRdrEachTrtFRRC <- as.vector(as.matrix(OR_FRRC$FRRC$ciAvgRdrEachTrt))
for (i in 1: length(dbmciAvgRdrEachTrtFRRC)){
x <- dbmciAvgRdrEachTrtFRRC[i]
y <- orciAvgRdrEachTrtFRRC[i]
expect_equal(x, y, tolerance = 0.001, scale = abs(x)) # values are not exactly equal
}
dbmciDiffTrtRRFC <- as.vector(as.matrix(DBM_RRFC$RRFC$ciDiffTrt))
orciDiffTrtRRFC <- as.vector(as.matrix(OR_RRFC$RRFC$ciDiffTrt))
for (i in 1: length(dbmciDiffTrtRRFC)){
x <- dbmciDiffTrtRRFC[i]
y <- orciDiffTrtRRFC[i]
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
dbmciAvgRdrEachTrtRRFC <- as.vector(as.matrix(DBM_RRFC$RRFC$ciAvgRdrEachTrt))
orciAvgRdrEachTrtRRFC <- as.vector(as.matrix(OR_RRFC$RRFC$ciAvgRdrEachTrt))
for (i in 1: length(dbmciAvgRdrEachTrtRRFC)){
x <- dbmciAvgRdrEachTrtRRFC[i]
y <- orciAvgRdrEachTrtRRFC[i]
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
})
contextStr <- "Compare DBM to OR for dataset05, FROC, wAFROC"
context(contextStr)
test_that(contextStr, {
ds <- dataset05
DBM_RRRC <- St(ds, FOM = "wAFROC", method = "DBM", analysisOption = "RRRC")
OR_RRRC <- St(ds, FOM = "wAFROC", method = "OR", analysisOption = "RRRC")
DBM_FRRC <- St(ds, FOM = "wAFROC", method = "DBM", analysisOption = "FRRC")
OR_FRRC <- St(ds, FOM = "wAFROC", method = "OR", analysisOption = "FRRC")
DBM_RRFC <- St(ds, FOM = "wAFROC", method = "DBM", analysisOption = "RRFC")
OR_RRFC <- St(ds, FOM = "wAFROC", method = "OR", analysisOption = "RRFC")
dbmfomArray <- DBM_RRRC$fomArray
orfomArray <- OR_RRRC$fomArray
for (i in 1: length(dbmfomArray)){
x <- as.numeric(dbmfomArray[[i]])
y <- as.numeric(orfomArray[[i]])
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
dbmFStatsRRRC <- as.vector(as.matrix(DBM_RRRC$RRRC$FTests))[-c(3,4,6,8)]
orFStatsRRRC <- as.vector(as.matrix(OR_RRRC$RRRC$FTests))[-c(3,4,6,8)]
names(orFStatsRRRC) <- NULL
for (i in 1: length(dbmFStatsRRRC)){
x <- as.numeric(dbmFStatsRRRC[[i]])
y <- as.numeric(orFStatsRRRC[[i]])
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
dbmFStatsFRRC <- DBM_FRRC$FRRC$FTests[1,4] # only check p-values
orFStatsFRRC <- OR_FRRC$FRRC$FTests[1,4]
names(orFStatsFRRC) <- NULL
for (i in 1: length(dbmFStatsFRRC)){
x <- as.numeric(dbmFStatsFRRC[[i]])
y <- as.numeric(orFStatsFRRC[[i]])
expect_equal(x, y, tolerance = 0.01, scale = abs(x))
}
dbmFStatsRRFC <- DBM_RRFC$RRFC$FTests[1,4] # only check p-values
orFStatsRRFC <- OR_RRFC$RRFC$FTests[1,4]
names(orFStatsRRFC) <- NULL
for (i in 1: length(dbmFStatsRRFC)){
x <- as.numeric(dbmFStatsRRFC[[i]])
y <- as.numeric(orFStatsRRFC[[i]])
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
# VarComp are not expected to be equal
dbmciDiffTrtRRRC <- as.vector(as.matrix(DBM_RRRC$RRRC$ciDiffTrt)) # remove 0-1 vs trt0-trt1
orciDiffTrtRRRC <- as.vector(as.matrix(OR_RRRC$RRRC$ciDiffTrt))
for (i in 1: length(dbmciDiffTrtRRRC)){
x <- dbmciDiffTrtRRRC[i]
y <- orciDiffTrtRRRC[i]
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
dbmciAvgRdrEachTrtRRRC <- as.vector(as.matrix(DBM_RRRC$RRRC$ciAvgRdrEachTrt))
orciAvgRdrEachTrtRRRC <- as.vector(as.matrix(OR_RRRC$RRRC$ciAvgRdrEachTrt))[-c(11,12)] # remove var comp
for (i in 1: length(dbmciAvgRdrEachTrtRRRC)){
x <- dbmciAvgRdrEachTrtRRRC[i]
y <- orciAvgRdrEachTrtRRRC[i]
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
dbmciDiffTrtFRRC <- as.vector(as.matrix(DBM_FRRC$FRRC$ciDiffTrt))[-c(3,4)]#[-c(1,2,4)] # remove DF and t values
orciDiffTrtFRRC <- as.vector(as.matrix(OR_FRRC$FRRC$ciDiffTrt))[-3] # remove z
for (i in 1: length(dbmciDiffTrtFRRC)){
x <- dbmciDiffTrtFRRC[i]
y <- orciDiffTrtFRRC[i]
expect_equal(x, y, tolerance = 0.01, scale = abs(x)) # values are not exactly equal; tolerance found by trial and error
}
dbmciAvgRdrEachTrtFRRC <- as.vector(as.matrix(DBM_FRRC$FRRC$ciAvgRdrEachTrt)) #[-c(1,2,7,8)])) # remove 0-1 vs trt0-trt1
orciAvgRdrEachTrtFRRC <- as.vector(as.matrix(OR_FRRC$FRRC$ciAvgRdrEachTrt)) #[-c(1,2,7,8)]))
for (i in 1: length(dbmciAvgRdrEachTrtFRRC)){
x <- dbmciAvgRdrEachTrtFRRC[i]
y <- orciAvgRdrEachTrtFRRC[i]
expect_equal(x, y, tolerance = 0.001, scale = abs(x)) # values are not exactly equal
}
dbmciDiffTrtRRFC <- as.vector(as.matrix(DBM_RRFC$RRFC$ciDiffTrt))
orciDiffTrtRRFC <- as.vector(as.matrix(OR_RRFC$RRFC$ciDiffTrt))
for (i in 1: length(dbmciDiffTrtRRFC)){
x <- dbmciDiffTrtRRFC[i]
y <- orciDiffTrtRRFC[i]
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
dbmciAvgRdrEachTrtRRFC <- as.vector(as.matrix(DBM_RRFC$RRFC$ciAvgRdrEachTrt)) #[-c(1,2)]) # remove 0-1 vs trt0-trt1
orciAvgRdrEachTrtRRFC <- as.vector(as.matrix(OR_RRFC$RRFC$ciAvgRdrEachTrt)) #[-c(1,2)])
for (i in 1: length(dbmciAvgRdrEachTrtRRFC)){
x <- dbmciAvgRdrEachTrtRRFC[i]
y <- orciAvgRdrEachTrtRRFC[i]
expect_equal(x, y, tolerance = 0.00001, scale = abs(x))
}
})
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