Nothing
test_that("equivalent approaches give same result", {
df <- data.frame(
tma = rep(1:2, times = 10),
biomarker = rep(1:2, times = 10) +
runif(max = 5, n = 20),
confounder = rep(0:1, times = 10) +
runif(max = 10, n = 20),
unity = 1
)
df_adj2 <- adjust_batch(
data = df,
markers = biomarker,
batch = tma,
method = simple,
suffix = "adj"
) |> # drop all attributes
data.frame()
df_adj3 <- adjust_batch(
data = df,
markers = biomarker,
batch = tma,
method = standardize,
confounders = unity,
suffix = "adj"
) |>
data.frame()
df_adj4 <- adjust_batch(
data = df,
markers = biomarker,
batch = tma,
method = ipw,
confounders = unity,
suffix = "adj"
) |>
data.frame()
expect_equal(df_adj2, df_adj3)
expect_equal(df_adj2, df_adj4)
})
test_that("multinomial model works", {
df <- data.frame(
tma = rep(1:3, times = 10),
biomarker = rep(1:2, times = 15) +
runif(max = 5, n = 30),
confounder = rep(0:1, times = 15) +
runif(max = 10, n = 30),
unity = 1
)
df_adj2 <- adjust_batch(
data = df,
markers = biomarker,
batch = tma,
method = simple,
suffix = "adj"
) |> # drop all attributes
data.frame()
df_adj4 <- adjust_batch(
data = df,
markers = biomarker,
batch = tma,
method = ipw,
confounders = unity,
suffix = "adj"
) |>
data.frame()
expect_equal(df_adj2, df_adj4)
})
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