Nothing
test_that("demean works", {
df <- iris
set.seed(123)
df$ID <- sample.int(4, nrow(df), replace = TRUE) # fake-ID
set.seed(123)
df$binary <- as.factor(rbinom(150, 1, 0.35)) # binary variable
set.seed(123)
x <- demean(
df,
select = c("Sepal.Length", "Petal.Length"),
by = "ID",
append = FALSE
)
expect_snapshot(head(x))
set.seed(123)
expect_message(
{
x <- demean(
df,
select = c("Sepal.Length", "binary", "Species"),
by = "ID",
append = FALSE
)
},
"have been coerced to numeric"
)
expect_snapshot(head(x))
set.seed(123)
expect_message(
{
y <- demean(
df,
select = ~ Sepal.Length + binary + Species,
by = ~ID,
append = FALSE
)
},
"have been coerced to numeric"
)
expect_message(
{
z <- demean(
df,
select = c("Sepal.Length", "binary", "Species"),
by = "ID",
append = FALSE
)
},
"have been coerced to numeric"
)
expect_identical(y, z)
set.seed(123)
x <- demean(df, select = c("Sepal.Length", "Petal.Length"), by = "ID")
expect_named(
x,
c(
"Sepal.Length",
"Sepal.Width",
"Petal.Length",
"Petal.Width",
"Species",
"ID",
"binary",
"Sepal.Length_between",
"Petal.Length_between",
"Sepal.Length_within",
"Petal.Length_within"
)
)
expect_snapshot(head(x))
df$Sepal.Length_within <- df$Sepal.Length
expect_error(
demean(df, select = c("Sepal.Length", "Petal.Length"), by = "ID"),
regex = "One or more of"
)
})
test_that("demean interaction term", {
dat <- data.frame(
a = c(1, 2, 3, 4, 1, 2, 3, 4),
x = c(4, 3, 3, 4, 1, 2, 1, 2),
y = c(1, 2, 1, 2, 4, 3, 2, 1),
ID = c(1, 2, 3, 1, 2, 3, 1, 2)
)
set.seed(123)
expect_snapshot(demean(
dat,
select = c("a", "x*y"),
by = "ID",
append = FALSE
))
})
test_that("demean shows message if some vars don't exist", {
dat <- data.frame(
a = c(1, 2, 3, 4, 1, 2, 3, 4),
x = c(4, 3, 3, 4, 1, 2, 1, 2),
y = c(1, 2, 1, 2, 4, 3, 2, 1),
ID = c(1, 2, 3, 1, 2, 3, 1, 2)
)
set.seed(123)
expect_error(
demean(dat, select = "foo", by = "ID"),
regexp = "not found"
)
})
# see issue #520
test_that("demean for cross-classified designs (by > 1)", {
skip_if_not_installed("poorman")
data(efc, package = "datawizard")
dat <- na.omit(efc)
dat$e42dep <- factor(dat$e42dep)
dat$c172code <- factor(dat$c172code)
x2a <- dat %>%
data_group(e42dep) %>%
data_modify(
c12hour_e42dep = mean(c12hour)
) %>%
data_ungroup() %>%
data_group(c172code) %>%
data_modify(
c12hour_c172code = mean(c12hour)
) %>%
data_ungroup() %>%
data_modify(
c12hour_within = c12hour - c12hour_e42dep - c12hour_c172code
)
out <- degroup(
dat,
select = "c12hour",
by = c("e42dep", "c172code"),
suffix_demean = "_within"
)
expect_equal(
out$c12hour_e42dep_between,
x2a$c12hour_e42dep,
tolerance = 1e-4,
ignore_attr = TRUE
)
expect_equal(
out$c12hour_within,
x2a$c12hour_within,
tolerance = 1e-4,
ignore_attr = TRUE
)
x2a <- dat %>%
data_group(e42dep) %>%
data_modify(
c12hour_e42dep = mean(c12hour, na.rm = TRUE),
neg_c_7_e42dep = mean(neg_c_7, na.rm = TRUE)
) %>%
data_ungroup() %>%
data_group(c172code) %>%
data_modify(
c12hour_c172code = mean(c12hour, na.rm = TRUE),
neg_c_7_c172code = mean(neg_c_7, na.rm = TRUE)
) %>%
data_ungroup() %>%
data_modify(
c12hour_within = c12hour - c12hour_e42dep - c12hour_c172code,
neg_c_7_within = neg_c_7 - neg_c_7_e42dep - neg_c_7_c172code
)
out <- degroup(
dat,
select = c("c12hour", "neg_c_7"),
by = c("e42dep", "c172code"),
suffix_demean = "_within"
)
expect_equal(
out$c12hour_e42dep_between,
x2a$c12hour_e42dep,
tolerance = 1e-4,
ignore_attr = TRUE
)
expect_equal(
out$neg_c_7_c172code_between,
x2a$neg_c_7_c172code,
tolerance = 1e-4,
ignore_attr = TRUE
)
expect_equal(
out$neg_c_7_within,
x2a$neg_c_7_within,
tolerance = 1e-4,
ignore_attr = TRUE
)
expect_equal(
out$c12hour_within,
x2a$c12hour_within,
tolerance = 1e-4,
ignore_attr = TRUE
)
# More than 2 groupings
mu <- 100
ul <- setNames(c(-1, -3, 0, 4), nm = letters[1:4])
uL <- setNames(c(10, 30, 0, -40), nm = LETTERS[1:4])
um <- setNames(c(100, 150, -250), nm = month.abb[1:3])
dat <- expand.grid(l = letters[1:4], L = LETTERS[1:4], m = month.abb[1:3])
set.seed(111)
e <- rnorm(nrow(dat) - 1) |> round(2)
e <- append(e, -sum(e))
dat$y <- mu + ul[dat$l] + uL[dat$L] + um[dat$m] + e
dat$z <- mu + ul[dat$l] + uL[dat$L] + um[dat$m] + 10 * e
dat_dem <- datawizard::demean(
dat,
by = c("l", "L", "m"),
select = c("y", "z")
)
expect_equal(dat_dem$y_l_between, ave(dat$y, dat$l), ignore_attr = TRUE)
expect_equal(dat_dem$y_L_between, ave(dat$y, dat$L), ignore_attr = TRUE)
expect_equal(dat_dem$y_m_between, ave(dat$y, dat$m), ignore_attr = TRUE)
expect_equal(rowSums(dat_dem[grepl("^y_", colnames(dat_dem))]), dat$y)
expect_equal(rowSums(dat_dem[grepl("^z_", colnames(dat_dem))]), dat$z)
})
test_that("demean, sanity checks", {
data(efc, package = "datawizard")
dat <- na.omit(efc)
dat$e42dep <- factor(dat$e42dep)
dat$c172code <- factor(dat$c172code)
expect_error(
degroup(
dat,
select = c("c12hour", "neg_c_8"),
by = c("e42dep", "c172code"),
suffix_demean = "_within"
),
regex = "Variable \"neg_c_8\" was not found"
)
expect_error(
degroup(
dat,
select = c("c12hour", "neg_c_8"),
by = c("e42dep", "c173code"),
suffix_demean = "_within"
),
regex = "Variables \"neg_c_8\" and \"c173code\" were not found"
)
})
test_that("demean for nested designs (by > 1), nested = TRUE", {
data(efc, package = "datawizard")
dat <- na.omit(efc)
dat$e42dep <- factor(dat$e42dep)
dat$c172code <- factor(dat$c172code)
x_ijk <- dat$c12hour
xbar_k <- ave(x_ijk, dat$e42dep, FUN = mean)
xbar_jk <- ave(x_ijk, dat$e42dep, dat$c172code, FUN = mean)
L3_between <- xbar_k
L2_between <- xbar_jk - xbar_k
L1_within <- x_ijk - xbar_jk
out <- degroup(
dat,
select = "c12hour",
by = c("e42dep", "c172code"),
nested = TRUE,
suffix_demean = "_within"
)
expect_equal(
out$c12hour_within,
L1_within,
tolerance = 1e-4,
ignore_attr = TRUE
)
expect_equal(
out$c12hour_e42dep_between,
L3_between,
tolerance = 1e-4,
ignore_attr = TRUE
)
expect_equal(
out$c12hour_c172code_between,
L2_between,
tolerance = 1e-4,
ignore_attr = TRUE
)
# Following #635
testdf <- data.frame(
roman = c("I", "I", "I", "I", "II", "II", "II", "II"),
alphabet = c("a", "a", "b", "b", "a", "b", "a", "b"),
val1 = c(1, 2, 3, 4, 5, 6, 7, 8),
val2 = c(1, 2, 3, 4, 5, 6, 7, 8),
val3 = c(1, 2, 3, 4, 5, 6, 7, 8)
)
out <- datawizard::demean(
testdf,
select = c("val1", "val2", "val3"),
by = "roman/alphabet",
append = FALSE
)
expect_named(
out,
c(
"val1_roman_between",
"val1_alphabet_between",
"val2_roman_between",
"val2_alphabet_between",
"val3_roman_between",
"val3_alphabet_between",
"val1_within",
"val2_within",
"val3_within"
)
)
expect_equal(
as.vector(out$val1_within),
c(-0.5, 0.5, -0.5, 0.5, -1, -1, 1, 1)
)
expect_equal(out$val1_within, out$val2_within)
expect_equal(out$val1_within, out$val3_within)
expect_equal(
as.vector(out$val1_roman_between),
c(2.5, 2.5, 2.5, 2.5, 6.5, 6.5, 6.5, 6.5)
)
expect_equal(out$val1_roman_between, out$val2_roman_between)
expect_equal(out$val1_roman_between, out$val3_roman_between)
expect_equal(
as.vector(out$val1_alphabet_between),
c(-1, -1, 1, 1, -0.5, 0.5, -0.5, 0.5)
)
expect_equal(out$val1_alphabet_between, out$val2_alphabet_between)
expect_equal(out$val1_alphabet_between, out$val3_alphabet_between)
expect_equal(rowSums(out[, grepl("^val1", names(out))]), testdf$val1)
})
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