suppressPackageStartupMessages({
library(dplyr)
})
test_that("simulate data", {
# Show that the function respects the seed and that
set.seed(120)
x <- simulate_test_data()
set.seed(120)
y <- simulate_test_data(
n = 200,
sd = c(3, 5, 7),
cor = c(0.1, 0.7, 0.4),
mu = list(
int = 10,
age = 3,
sex = 2,
trt = c(0, 4, 8),
visit = c(0, 1, 2)
)
)
set.seed(121)
z <- simulate_test_data()
expect_true(identical(x, y))
expect_false(identical(x, z))
# Show that we can recover known values
set.seed(3918)
dat <- simulate_test_data(
n = 4000,
sd = c(1, 2, 3),
cor = c(0, 0, 0.),
mu = list(
int = 10,
age = 3,
sex = 2,
trt = c(0, 8, 17),
visit = c(0, 3, 6)
)
)
mod <- lm(data = dat, outcome ~ age + sex + group * visit)
m <- coef(mod)
v <- sqrt(diag(vcov(mod)))
lci <- m - qnorm(0.99) * v
uci <- m + qnorm(0.99) * v
real <- c(10, 3, 2, 0, 3, 6, 8, 17)
expect_true(all(lci <= real & real <= uci))
})
test_that("vcov", {
actual <- as_vcov(c(1, 2), 0)
expected <- matrix(c(1, 0, 0, 4), byrow = TRUE, nrow = 2)
expect_equal(actual, expected)
actual <- as_vcov(c(2, 4), 0.5)
expected <- matrix(c(4, 4, 4, 16), byrow = TRUE, nrow = 2)
expect_equal(actual, expected)
actual <- as_vcov(c(2, 4, 8), c(0.4, 0.5, 0.6))
expected <- matrix(
c(4, 3.2, 8,
3.2, 16, 19.2,
8, 19.2, 64),
byrow = TRUE,
nrow = 3
)
expect_equal(actual, expected)
})
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