Nothing
data("exampleData1")
Data <- exampleData1[-c(83:138), ]
markers <- Data[, -1]
status <- factor(Data$group, levels = c("not_needed", "needed"))
test <- exampleData1[c(83:138), ]
load("result_data/mayo.rda")
Data2 <- mayo[-c(42:119), ]
markers2 <- Data2[, 3:4]
status2 <- factor(Data2[, 2], levels = c(1, 0))
Data3 <-
read.csv(
"result_data/wdbc.data.txt",
header = FALSE
)
Data3 <- Data3[-c(121:262), ]
markers3 <- Data3[, 4:5]
status3 <- factor(Data3[, 2], levels = c("B", "M"))
###############################################################################
load("result_data/test_linComb.rda")
for (method in c(
"TS",
"minimax"
)) {
set.seed(14042022)
res <- linComb(
markers = markers,
status = status,
event = "needed",
method = method,
resample = "none",
direction = "<",
cutoff.method = "Youden"
)
test_that("linComb functions ...", {
expect_length(res, 15)
expect_equal(as.numeric(res$CombScore), r$Comb.score[r$Method == method],
tolerance =
0.1
)
expect_equal(as.numeric(res$AUC_table$AUC[[3]]), r$AUC[r$Method == method][1],
tolerance =
0.01
)
expect_equal(as.numeric(res$DiagStatCombined$detail[4, 2]),
r$SPE[r$Method == method][1],
tolerance = 0.01
)
expect_equal(as.numeric(res$DiagStatCombined$detail[3, 2]),
r$SENS[r$Method == method][1],
tolerance = 0.01
)
expect_equal(as.numeric(res$ThresholdCombined), r$Cutoff[r$Method == method][1],
tolerance =
0.01
)
})
}
###############################################################################
for (method in c(
"logistic",
"SL",
"scoring"
)) {
set.seed(14042022)
res <- linComb(
markers = markers2,
status = status2,
event = "1",
method = method,
resample = "none",
direction = "<",
cutoff.method = "Youden"
)
test_that("linComb functions ...", {
expect_length(res, 15)
expect_equal(as.numeric(res$CombScore), r$Comb.score[r$Method == method],
tolerance =
0.1
)
expect_equal(as.numeric(res$AUC_table$AUC[[3]]), r$AUC[r$Method == method][1],
tolerance =
0.01
)
expect_equal(as.numeric(res$DiagStatCombined$detail[4, 2]),
r$SPE[r$Method == method][1],
tolerance = 0.01
)
expect_equal(as.numeric(res$DiagStatCombined$detail[3, 2]),
r$SENS[r$Method == method][1],
tolerance = 0.01
)
expect_equal(as.numeric(res$ThresholdCombined), r$Cutoff[r$Method == method][1],
tolerance =
0.01
)
})
}
###############################################################################
for (method in c(
"PCL",
"PT",
"minmax"
)) {
set.seed(14042022)
res <- linComb(
markers = markers3,
status = status3,
event = "M",
method = method,
resample = "none",
standardize = "range",
direction = "<",
cutoff.method = "Youden"
)
test_that("linComb functions ...", {
expect_length(res, 15)
expect_equal(as.numeric(res$CombScore), r$Comb.score[r$Method == method],
tolerance =
0.1
)
expect_equal(as.numeric(res$AUC_table$AUC[[3]]), r$AUC[r$Method == method][1],
tolerance =
0.01
)
expect_equal(as.numeric(res$DiagStatCombined$detail[4, 2]),
r$SPE[r$Method == method][1],
tolerance = 0.01
)
expect_equal(as.numeric(res$DiagStatCombined$detail[3, 2]),
r$SENS[r$Method == method][1],
tolerance = 0.01
)
expect_equal(as.numeric(res$ThresholdCombined), r$Cutoff[r$Method == method][1],
tolerance =
0.01
)
})
}
###############################################################################
status4 <- factor(Data3[, 2], levels = c("B", "M", "C"))
status4[[9]] <- "C"
test_that("linComb functions ...", {
expect_error(
linComb(
markers = Data3[, 4:5],
status = status4,
event = "M",
method = "scoring",
direction = direction,
standardize = "zScore",
cutoff.method = cutoff.method
),
"the number of status levels should be 2"
)
expect_error(
linComb(
markers = Data3[, 4:6],
status = status3,
event = "M",
method = "PT",
direction = direction,
standardize = "zScore",
cutoff.method = cutoff.method
),
"the number of markers should be 2"
)
})
test_that("linComb functions ...", {
expect_error(
linComb(
markers = markers3,
status = status3,
event = "M",
direction = "<",
standardize = "none",
cutoff.method = "Youden"
),
"method should be one of 'scoring', 'SL', 'logistic', 'minmax', 'PT', 'PCL', 'minimax', 'TS'"
)
expect_error(
linComb(
markers = markers3,
status = status3,
event = "M",
method = "asaddsa",
direction = "auto",
standardize = "none",
cutoff.method = "Youden"
),
"method should be one of 'scoring', 'SL', 'logistic', 'minmax', 'PT', 'PCL', 'minimax', 'TS'"
)
expect_error(
linComb(
markers = markers3,
status = status3,
event = "M",
method = "minmax",
direction = "auto",
resample = "cv",
standardize = "asdada",
cutoff.method = "Youden"
),
"standardize should be one of 'range', 'zScore', 'tScore', 'mean', 'deviance'"
)
expect_error(
linComb(
markers = markers2,
status = status2,
event = "1",
method = "minimax",
direction = "asdada",
standardize = "none",
cutoff.method = "Youden"
),
"direction should be one of 'auto', '<', '>'"
)
expect_error(
linComb(
markers = markers2,
status = status2,
event = "1",
method = "SL",
direction = "auto",
standardize = "tScore",
cutoff.method = "sadda"
),
"The entered cutoff.method is invalid"
)
expect_error(
linComb(
markers = markers2,
status = status2,
event = "1",
method = "scoring",
resample = "sada",
standardize = "range",
direction = "<",
cutoff.method = "Youden"
),
"resample should be one of 'none', 'cv', 'repeatedcv', 'boot'"
)
})
###############################################################################
markers3[44, 1:2] <- "assay"
test_that("linComb functions ...", {
expect_error(
linComb(
markers = markers3,
status = status3,
event = "M",
method = "PCL",
direction = "<",
standardize = "zScore",
cutoff.method = "Youden"
),
"at least one variable is not numeric"
)
expect_error(
linComb(
markers = markers,
status = status,
event = "C",
method = "PCL",
direction = "<",
standardize = "zScore",
cutoff.method = "Youden"
),
"status does not include event"
)
})
###############################################################################
markers3 <- Data3[, 4:5]
status3[[12]] <- NA
test_that("linComb functions ...", {
expect_warning(
linComb(
markers = markers3,
status = status3,
event = "M",
method = "TS",
direction = "<",
standardize = "zScore",
cutoff.method = "Youden"
),
"Rows with NA removed from the dataset since status include NA"
)
})
markers3[44, 1:2] <- NA
status3 <- factor(Data3[, 2], levels = c("B", "M"))
test_that("linComb functions ...", {
expect_warning(
linComb(
markers = markers3,
status = status3,
event = "M",
method = "TS",
direction = "<",
standardize = "zScore",
cutoff.method = "Youden"
),
"Rows with NA removed from the dataset since markers include NA"
)
})
test_that("linComb functions ...", {
expect_warning(
linComb(
markers = markers,
status = status,
event = "needed",
method = "PCL",
direction = "<",
cutoff.method = "Youden"
),
"The used combination method requires range standardization. All biomarker values are standardized to a range between 0 and 1."
)
})
test_that("linComb functions ...", {
expect_warning(
linComb(
markers = markers,
status = status,
event = "needed",
method = "PT",
direction = "<",
cutoff.method = "Youden"
),
"The used combination method requires zScore standardization."
)
})
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