context("test-correlations")
# Read test results
test_results <- read_stats("test_results.csv")
# Run tests, consisting of the following steps:
# - Retrieve the correct output from the test results file
# - Run the statistical model
# - Tidy the output
# - Compare the tidied output with the (correct) output from the file
test_that("pearson correlations work", {
correct <- test_results[["correlation_pearson"]]
model <- cor.test(cox$call_parent, cox$anxiety, method = "pearson")
output <- tidy_stats(model)
expect_equal(as.data.frame(output), as.data.frame(correct), tolerance = .002)
})
test_that("kendall correlations work", {
correct <- test_results[["correlation_kendall"]]
model <- cor.test(cox$call_parent, cox$anxiety, method = "kendall")
output <- tidy_stats(model)
expect_equal(as.data.frame(output), as.data.frame(correct), tolerance = .002)
})
test_that("spearman correlations work", {
correct <- test_results[["correlation_spearman"]]
model <- suppressWarnings(cor.test(cox$call_parent, cox$anxiety,
method = "spearman"))
output <- tidy_stats(model)
expect_equal(as.data.frame(output), as.data.frame(correct), tolerance = .002)
})
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