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skip_if_not_installed("withr")
# make sure we have the correct interaction mark for tests
withr::with_options(
list(parameters_interaction = "*", easystats_table_width = Inf),
{
data(iris)
m1 <- lm(Sepal.Length ~ Species, data = iris)
m2 <- lm(Sepal.Length ~ Species * Petal.Length, data = iris)
counts <- c(18, 17, 15, 20, 10, 20, 25, 13, 12)
outcome <- gl(3, 1, 9)
treatment <- gl(3, 3)
m3 <- glm(counts ~ outcome + treatment, family = poisson())
x <- compare_parameters(m1, m2, m3)
test_that("compare_parameters, default", {
expect_identical(
colnames(x),
c(
"Parameter", "Component", "Effects", "Coefficient.m1", "SE.m1", "CI.m1",
"CI_low.m1", "CI_high.m1", "t.m1", "df_error.m1", "p.m1", "Coefficient.m2",
"SE.m2", "CI.m2", "CI_low.m2", "CI_high.m2", "t.m2", "df_error.m2",
"p.m2", "Log-Mean.m3", "SE.m3", "CI.m3", "CI_low.m3", "CI_high.m3",
"z.m3", "df_error.m3", "p.m3"
)
)
out <- capture.output(x)
expect_length(out, 14)
out <- format(x, select = "ci")
expect_identical(colnames(out), c("Parameter", "m1", "m2", "m3"))
expect_identical(
out$Parameter,
c(
"(Intercept)", "Species [versicolor]", "Species [virginica]",
"Petal Length", "Species [versicolor] * Petal Length",
"Species [virginica] * Petal Length", "outcome [2]", "outcome [3]",
"treatment [2]", "treatment [3]", NA, "Observations"
)
)
})
x <- compare_parameters(m1, m2, m3, select = "se_p2")
test_that("compare_parameters, se_p2", {
expect_identical(
colnames(x),
c(
"Parameter", "Component", "Effects", "Coefficient.m1", "SE.m1", "CI.m1",
"CI_low.m1", "CI_high.m1", "t.m1", "df_error.m1", "p.m1", "Coefficient.m2",
"SE.m2", "CI.m2", "CI_low.m2", "CI_high.m2", "t.m2", "df_error.m2",
"p.m2", "Log-Mean.m3", "SE.m3", "CI.m3", "CI_low.m3", "CI_high.m3",
"z.m3", "df_error.m3", "p.m3"
)
)
out <- capture.output(x)
expect_length(out, 14)
out <- format(x, select = "se_p2")
expect_identical(
colnames(out),
c(
"Parameter", "Estimate (SE) (m1)", "p (m1)", "Estimate (SE) (m2)",
"p (m2)", "Estimate (SE) (m3)", "p (m3)"
)
)
expect_identical(
out$Parameter,
c(
"(Intercept)", "Species [versicolor]", "Species [virginica]",
"Petal Length", "Species [versicolor] * Petal Length",
"Species [virginica] * Petal Length", "outcome [2]", "outcome [3]",
"treatment [2]", "treatment [3]", NA, "Observations"
)
)
})
data(mtcars)
m1 <- lm(mpg ~ wt, data = mtcars)
m2 <- glm(vs ~ wt + cyl, data = mtcars, family = "binomial")
test_that("compare_parameters, column name with escaping regex characters", {
out <- utils::capture.output(compare_parameters(m1, m2, column_names = c("linear model (m1)", "logistic reg. (m2)")))
expect_identical(out[1], "Parameter | linear model (m1) | logistic reg. (m2)")
})
data(mtcars)
m1 <- lm(mpg ~ hp, mtcars)
m2 <- lm(mpg ~ hp, mtcars)
test_that("compare_parameters, proper printing for CI=NULL #820", {
expect_snapshot(compare_parameters(m1, m2, ci = NULL))
})
skip_on_cran()
test_that("compare_parameters, correct random effects", {
suppressWarnings(skip_if_not_installed("glmmTMB"))
skip_if_not(getRversion() >= "4.0.0")
data("fish")
m0 <- glm(count ~ child + camper, data = fish, family = poisson())
m1 <- glmmTMB::glmmTMB(
count ~ child + camper + (1 | persons) + (1 | ID),
data = fish,
family = poisson()
)
m2 <- glmmTMB::glmmTMB(
count ~ child + camper + zg + (1 | ID),
ziformula = ~ child + (1 | persons),
data = fish,
family = glmmTMB::truncated_poisson()
)
cp <- compare_parameters(m0, m1, m2, effects = "all", component = "all")
expect_snapshot(cp)
})
test_that("compare_parameters, print_md", {
skip_if_not_installed("lme4")
data(sleepstudy, package = "lme4")
set.seed(1234)
sleepstudy$grp <- as.factor(sample.int(3, nrow(sleepstudy), replace = TRUE))
lm1 <- lme4::lmer(Reaction ~ Days + grp + (1 | Subject), data = sleepstudy)
lm2 <- lme4::lmer(Reaction ~ Days * grp + (1 | Subject), data = sleepstudy)
cp <- compare_parameters(lm1, lm2, select = "{estimate} ({ci})|{p}", drop = "^\\(Intercept")
out <- print_md(cp, groups = list(
Groups = c("grp (2)", "grp (3)"),
Interactions = c("Days * grp (2)", "Days * grp (3)"),
Controls = "Days"
))
expect_snapshot(print(out))
cp <- compare_parameters(lm1, lm2, select = "{estimate} ({ci})|{p}", drop = "^\\(Intercept", effects = "all")
expect_snapshot(print_md(cp))
# error
expect_error(
print_md(cp, groups = list(
Groups = c("grp (2)", "grp (3)"),
Interactions = c("Days * grp (2)", "Days * grp (3)"),
Controls = "Days"
)),
regex = "Cannot combine"
)
# with reference level
cp <- compare_parameters(lm1, lm2, select = "{estimate} ({ci})|{p}", drop = "^\\(Intercept", include_reference = TRUE)
out <- print_md(cp, groups = list(
Groups = 2:4,
Interactions = 5:6,
Controls = 1
))
expect_snapshot(print(out))
# with reference level
cp <- compare_parameters(lm1, lm2, drop = "^\\(Intercept", include_reference = TRUE)
out <- print_md(cp, groups = list(
Groups = 2:4,
Interactions = 5:6,
Controls = 1
))
expect_snapshot(print(out))
# error
cp <- compare_parameters(lm1, lm2, select = "{estimate} ({ci})|{p}", drop = "^\\(Intercept")
expect_error(
print_md(cp, groups = list(
Groups = c("grp (2)", "grp (3)"),
Interactions = c("Days * grp (2)", "Days * grp (3)"),
Controls = "XDays"
)),
regex = "Some group indices"
)
expect_error(
print_md(cp, groups = list(
Groups = 1:2,
Interactions = 4:5,
Controls = 10
)),
regex = "Some group indices"
)
# output identical for both calls
cp1 <- compare_parameters(lm1, lm2, select = "{estimate} ({ci})|{p}", drop = "^\\(Intercept")
out1 <- capture.output(print_md(cp1, groups = list(
Groups = c("grp (2)", "grp (3)"),
Interactions = c("Days * grp (2)", "Days * grp (3)"),
Controls = "Days"
)))
cp2 <- compare_parameters(
lm1,
lm2,
select = "{estimate} ({ci})|{p}",
drop = "^\\(Intercept",
groups = list(
Groups = c("grp (2)", "grp (3)"),
Interactions = c("Days * grp (2)", "Days * grp (3)"),
Controls = "Days"
)
)
out2 <- capture.output(print_md(cp2))
expect_identical(out1, out2)
})
}
)
skip_on_cran()
skip_if_not_installed("blme")
skip_if_not_installed("glmmTMB")
skip_if_not_installed("lme4")
test_that("compare_parameters, works with blmer and glmmTMB", {
data(sleepstudy, package = "lme4")
control <- lme4::lmerControl(check.conv.grad = "ignore")
fm1 <- blme::blmer(Reaction ~ Days + (0 + Days | Subject), sleepstudy,
control = control,
cov.prior = gamma
)
fm2 <- glmmTMB::glmmTMB(Reaction ~ Days + (1 + Days | Subject), sleepstudy)
expect_silent(compare_parameters(fm1, fm2))
})
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