Nothing
context("biomarkertmle estimation function.")
library(dplyr)
library(biotmleData)
library(SuperLearner)
library(SummarizedExperiment)
data(illuminaData)
## SETUP TESTS #################################################################
colData(illuminaData) <- colData(illuminaData) %>%
data.frame() %>%
dplyr::mutate(age = as.numeric(age > median(age))) %>%
DataFrame()
varInt_index <- which(names(colData(illuminaData)) %in% "benzene")
biomarkerTMLEout <- biomarkertmle(
se = illuminaData[1:2, ],
varInt = varInt_index,
parallel = FALSE,
g_lib = c("SL.mean", "SL.glm"),
Q_lib = "SL.mean"
)
## BEGIN TESTS #################################################################
test_that("biomarkertmle output object is of class type S4", {
expect_equivalent(typeof(biomarkerTMLEout), "S4")
})
test_that("biomarkertmle object is of appropriate custom class", {
expect_equivalent(class(biomarkerTMLEout), "bioTMLE")
})
test_that("biomarkertmle output is consistent using example data", {
expect_equal(
assay(biomarkerTMLEout)[1, c(17, 83, 117)],
c(360.7073, 375.9316, 319.3649)
)
})
test_that("biomarkertmle output returns IC estimate for each subject", {
expect_equal(ncol(assay(biomarkerTMLEout)), ncol(illuminaData))
})
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