testthat::context('corrpart')
testthat::test_that('All options in the corrPart work for partial correlation (sunny)', {
df <- data.frame(
`var 1` = c(8, 51, 2, 74, 1, 91, 5, 25, 1, 59, 5, 32, 7),
`var 2` = c(2, NA, NaN, 3, -1, -2, 1, 1, -2, 2, -2, -3, 3),
`var 3` = c(0, 4, 19, 5, 9, 15, 1, 4, 19, 10, 13, 7, 5),
check.names = FALSE
)
r <- jmv::corrPart(
data = df,
vars = c("var 1", "var 2"),
controls = "var 3",
type = "part",
spearman = TRUE,
kendall = TRUE,
n = TRUE
)
# Test correlation table
corTable <- r$matrix
# Test Pearson's r
testthat::expect_equal(
0.254, as.numeric(corTable$getCell(rowKey="var 2", "var 1[r]")$value), tolerance = 1e-3
)
# Test Pearson's r p-value
testthat::expect_equal(
0.478, as.numeric(corTable$getCell(rowKey="var 2", "var 1[rp]")$value), tolerance = 1e-3
)
# Test Spearman's rho
testthat::expect_equal(
0.197, as.numeric(corTable$getCell(rowKey="var 2", "var 1[rho]")$value), tolerance = 1e-3
)
# Test Spearman's rho p-value
testthat::expect_equal(
0.586, as.numeric(corTable$getCell(rowKey="var 2", "var 1[rhop]")$value), tolerance = 1e-3
)
# Test Kendall's tau
testthat::expect_equal(
0.193, as.numeric(corTable$getCell(rowKey="var 2", "var 1[tau]")$value), tolerance = 1e-3
)
# Test Kendall's tau p-value
testthat::expect_equal(
0.436, as.numeric(corTable$getCell(rowKey="var 2", "var 1[taup]")$value), tolerance = 1e-3
)
# Test N
testthat::expect_equal(11, as.numeric(corTable$getCell(rowKey="var 2", "var 1[n]")$value))
})
testthat::test_that('All options in the corrPart work for semipartial correlation (sunny)', {
df <- data.frame(
`var 1` = c(8, 51, 2, 74, 1, 91, 5, 25, 1, 59, 5, 32, 7),
`var 2` = c(2, NA, NaN, 3, -1, -2, 1, 1, -2, 2, -2, -3, 3),
`var 3` = c(0, 4, 19, 5, 9, 15, 1, 4, 19, 10, 13, 7, 5),
check.names = FALSE
)
r <- jmv::corrPart(
data = df,
vars = c("var 1", "var 2"),
controls = "var 3",
type = "semi",
spearman = TRUE,
kendall = TRUE,
n = TRUE
)
# Test correlation table
corTable <- r$matrix
# Test Pearson's r
testthat::expect_equal(
0.194, as.numeric(corTable$getCell(rowKey="var 2", "var 1[r]")$value), tolerance = 1e-3
)
testthat::expect_equal(
0.251, as.numeric(corTable$getCell(rowKey="var 1", "var 2[r]")$value), tolerance = 1e-3
)
# Test Pearson's r p-value
testthat::expect_equal(
0.591, as.numeric(corTable$getCell(rowKey="var 2", "var 1[rp]")$value), tolerance = 1e-3
)
testthat::expect_equal(
0.484, as.numeric(corTable$getCell(rowKey="var 1", "var 2[rp]")$value), tolerance = 1e-3
)
# Test Spearman's rho
testthat::expect_equal(
0.162, as.numeric(corTable$getCell(rowKey="var 2", "var 1[rho]")$value), tolerance = 1e-3
)
testthat::expect_equal(
0.196, as.numeric(corTable$getCell(rowKey="var 1", "var 2[rho]")$value), tolerance = 1e-3
)
# Test Spearman's rho p-value
testthat::expect_equal(
0.656, as.numeric(corTable$getCell(rowKey="var 2", "var 1[rhop]")$value), tolerance = 1e-3
)
testthat::expect_equal(
0.587, as.numeric(corTable$getCell(rowKey="var 1", "var 2[rhop]")$value), tolerance = 1e-3
)
# Test Kendall's tau
testthat::expect_equal(
0.177, as.numeric(corTable$getCell(rowKey="var 2", "var 1[tau]")$value), tolerance = 1e-3
)
testthat::expect_equal(
0.193, as.numeric(corTable$getCell(rowKey="var 1", "var 2[tau]")$value), tolerance = 1e-3
)
# Test Kendall's tau p-value
testthat::expect_equal(
0.477, as.numeric(corTable$getCell(rowKey="var 2", "var 1[taup]")$value), tolerance = 1e-3
)
testthat::expect_equal(
0.436, as.numeric(corTable$getCell(rowKey="var 1", "var 2[taup]")$value), tolerance = 1e-3
)
# Test N
testthat::expect_equal(11, as.numeric(corTable$getCell(rowKey="var 2", "var 1[n]")$value))
testthat::expect_equal(11, as.numeric(corTable$getCell(rowKey="var 1", "var 2[n]")$value))
})
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