tests/testthat/test-01.R

In OHDSI/MethodEvaluation: Package for Evaluation of Estimation Methods

library(testthat)
library(dplyr)

connectionDetails <- Eunomia::getEunomiaConnectionDetails()
Eunomia::createCohorts(connectionDetails)

test_that("Compute MDRR", {
  result <- computeMdrr(
    connectionDetails = connectionDetails,
    cdmDatabaseSchema = "main",
    exposureOutcomePairs = data.frame(
      exposureId = c(1, 2),
      outcomeId = c(4, 5)
    ),
    exposureTable = "cohort",
    outcomeTable = "cohort"
  )

  expect_equal(ncol(result), 7)
  # TODO: need to check results (that are currently empty)
})

test_that("Synthesize positive controls", {
  expect_error(
    suppressWarnings(
      synthesizePositiveControls(
        connectionDetails = connectionDetails,
        cdmDatabaseSchema = "main",
        exposureOutcomePairs = data.frame(
          exposureId = c(1),
          outcomeId = c(4)
        )
      )
    ),
    "Not enough negative controls"
  )

  # TODO: need to check an actual synthesis

  expect_error(
    suppressWarnings(
      injectSignals(
        connectionDetails = connectionDetails,
        cdmDatabaseSchema = "main",
        exposureOutcomePairs = data.frame(
          exposureId = c(1),
          outcomeId = c(4)
        )
      )
    ),
    "Not enough negative controls"
  )
})

test_that("Create reference set cohort", {
  tempFolder <- tempfile()
  dir.create(tempFolder)
  createReferenceSetCohorts(
    connectionDetails = connectionDetails,
    cdmDatabaseSchema = "main",
    referenceSet = "omopReferenceSet",
    workFolder = tempFolder
  )

  # TODO Need a check for completion

  createReferenceSetCohorts(
    connectionDetails = connectionDetails,
    cdmDatabaseSchema = "main",
    referenceSet = "ohdsiMethodsBenchmark",
    workFolder = tempFolder
  )
  cohortCounts <- read.csv(file.path(tempFolder, "cohortCounts.csv"))
  controls <- readRDS(system.file("ohdsiNegativeControls.rds",
    package = "MethodEvaluation"
  )) %>%
    filter(.data$outcomeId > 4) %>%
    distinct(cohortId = .data$outcomeId)
  expect_equal(
    nrow(cohortCounts %>% filter(type == "Outcome")),
    nrow(controls) + 4
  ) # adding c("acute_pancreatitis", "gi_bleed", "stroke", "ibd")

  createReferenceSetCohorts(
    connectionDetails = connectionDetails,
    cdmDatabaseSchema = "main",
    referenceSet = "ohdsiDevelopment",
    workFolder = tempFolder
  )
  cohortCounts <- read.csv(file.path(tempFolder, "cohortCounts.csv"))
  controls <- readRDS(system.file("ohdsiDevelopmentNegativeControls.rds",
    package = "MethodEvaluation"
  ))
  expect_equal(
    nrow(cohortCounts %>% filter(type == "Outcome")),
    nrow(controls)
  )
  unlink(tempFolder, recursive = TRUE)
})


test_that("Synthesize positive control reference set cohort", {
  tempFolder <- tempfile()
  dir.create(tempFolder)
  expect_error(
    suppressWarnings(
      synthesizeReferenceSetPositiveControls(
        connectionDetails = connectionDetails,
        cdmDatabaseSchema = "main",
        referenceSet = "ohdsiMethodsBenchmark",
        workFolder = tempFolder
      )
    ),
    "Not enough negative controls"
  )
  expect_error(
    suppressWarnings(
      synthesizeReferenceSetPositiveControls(
        connectionDetails = connectionDetails,
        cdmDatabaseSchema = "main",
        referenceSet = "ohdsiDevelopment",
        workFolder = tempFolder
      )
    ),
    "Not enough negative controls"
  )
  unlink(tempFolder, recursive = TRUE)
})