pkgs <- c("insight", "estimatr", "ivreg")
invisible(sapply(pkgs, requiet))
test_that("Issue #612: factor padding", {
# stats::model.matrix() breaks on contrasts when a column of `data` has
# only 1 factor level
# no factor
mod <- glm(vs ~ cyl, data = mtcars, family = binomial)
mm <- get_modelmatrix(mod)
expect_equal(nrow(mm), 32)
mm <- get_modelmatrix(mod, data = mtcars)
expect_equal(nrow(mm), 32)
mm <- get_modelmatrix(mod, data = head(mtcars))
expect_equal(nrow(mm), 6)
# one factor
dat <- mtcars
dat$cyl <- factor(dat$cyl)
mod <- glm(vs ~ cyl, data = dat, family = binomial)
# no data argument
mm <- get_modelmatrix(mod)
expect_equal(nrow(mm), 32)
# enough factor levels
mm <- get_modelmatrix(mod, data = head(dat))
expect_equal(nrow(mm), 6)
# not enough factor levels
mm <- get_modelmatrix(mod, data = dat[3, ])
expect_equal(nrow(mm), 1)
})
# iv_robust --------------------------------------------------------------
# =========================================================================
test_that("get_modelmatrix - iv_robust", {
data(Kmenta, package = "ivreg")
x <- iv_robust(Q ~ P + D | D + F + A, se_type = "stata", data = Kmenta)
out1 <- get_modelmatrix(x)
out2 <- model.matrix(terms(x), data = Kmenta)
expect_equal(out1, out2, tolerance = 1e-3, ignore_attr = TRUE)
out1 <- get_modelmatrix(x, data = get_datagrid(x, at = "P"))
out2 <- model.matrix(terms(x), data = get_datagrid(x, at = "P", include_response = TRUE))
expect_equal(out1, out2, tolerance = 1e-3, ignore_attr = TRUE)
expect_equal(nrow(get_datagrid(x, at = "P")), nrow(out2))
})
# ivreg --------------------------------------------------------------
# ====================================================================
test_that("get_modelmatrix - ivreg", {
data(Kmenta, package = "ivreg")
x <- ivreg(Q ~ P + D | D + F + A, data = Kmenta)
out1 <- get_modelmatrix(x)
out2 <- model.matrix(x, data = Kmenta)
expect_equal(out1, out2, tolerance = 1e-3, ignore_attr = TRUE)
out1 <- get_modelmatrix(x, data = get_datagrid(x, at = "P"))
out2 <- model.matrix(terms(x), data = get_datagrid(x, at = "P", include_response = TRUE))
expect_equal(out1, out2, tolerance = 1e-3, ignore_attr = TRUE)
expect_equal(nrow(get_datagrid(x, at = "P")), nrow(out2))
})
# ivreg --------------------------------------------------------------
# ====================================================================
test_that("get_modelmatrix - lm_robust", {
set.seed(15)
N <- 1:40
dat <<- data.frame(
N = N,
y = rpois(N, lambda = 4),
x = rnorm(N),
z = rbinom(N, 1, prob = 0.4)
)
x <- lm_robust(y ~ x + z, data = dat)
out1 <- get_modelmatrix(x)
out2 <- model.matrix(x, data = dat)
expect_equal(out1, out2, tolerance = 1e-3, ignore_attr = TRUE)
out1 <- get_modelmatrix(x, data = get_datagrid(x, at = "x"))
out2 <- model.matrix(x, data = get_datagrid(x, at = "x", include_response = TRUE))
expect_equal(out1, out2, tolerance = 1e-3, ignore_attr = TRUE)
expect_equal(nrow(get_datagrid(x, at = "x")), nrow(out2))
})
test_that("Issue #693", {
set.seed(12345)
n <- 500
x <- sample(1:3, n, replace = TRUE)
w <- sample(1:4, n, replace = TRUE)
y <- rnorm(n)
z <- ifelse(x + y + rlogis(n) > 1.5, 1, 0)
dat <<- data.frame(x = factor(x), w = factor(w), y = y, z = z)
m <- glm(z ~ x + w + y, family = binomial, data = dat)
nd <- head(dat, 2)
mm <- get_modelmatrix(m, data = head(dat, 1))
expect_true(all(c("x2", "x3", "w2", "w3", "w4") %in% colnames(mm)))
})
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