# lqm -----------------------
test_that("model_parameters - lqm", {
skip_if_not_installed("lqmm")
# data
set.seed(123)
n <- 500
p <- 1:3 / 4
set.seed(123)
x <- runif(n, 0, 1)
y <- 30 + x + rnorm(n)
test <<- data.frame(x, y)
# model
set.seed(123)
fit.lqm <-
lqmm::lqm(
y ~ x,
data = test,
tau = p,
control = list(verbose = FALSE, loop_tol_ll = 1e-9),
fit = TRUE
)
df_lqm <- as.data.frame(model_parameters(fit.lqm))
expect_equal(df_lqm$Coefficient,
c(
29.3220715172958, 1.1244506550584, 29.9547605920406, 1.1822574944936,
30.6283792821576, 1.25165747424685
),
tolerance = 0.001
)
})
# lqmm -----------------------
test_that("model_parameters - lqmm", {
skip("TODO: fix this test")
skip_if_not_installed("lqmm")
# setup
set.seed(123)
# data
M <- 50
n <- 10
set.seed(123)
x <- runif(n * M, 0, 1)
group <- rep(1:M, each = n)
y <- 10 * x + rep(rnorm(M, 0, 2), each = n) + rchisq(n * M, 3)
test <<- data.frame(x, y, group)
# model
set.seed(123)
fit.lqmm <-
lqmm::lqmm(
fixed = y ~ x,
random = ~1,
group = group,
data = test,
tau = 0.5,
nK = 11,
type = "normal"
)
df_lqmm <- as.data.frame(model_parameters(fit.lqmm))
expect_equal(df_lqmm,
structure(
list(
Parameter = c("(Intercept)", "x"),
Coefficient = c(
3.44347538706013,
9.25833091219961
),
SE = c(0.491049614414579, 0.458163772053399),
CI = c(0.95, 0.95),
CI_low = c(2.47868633791118, 8.35815427623814),
CI_high = c(4.40826443620908, 10.1585075481611),
t = c(
7.01247956617455,
20.207470509302
),
df_error = c(497L, 497L),
p = c(
6.34497395571023e-09,
2.05172540270515e-25
)
),
row.names = 1:2,
pretty_names = c(
`(Intercept)` = "(Intercept)",
x = "x"
),
ci = 0.95,
verbose = TRUE,
exponentiate = FALSE,
ordinal_model = FALSE,
linear_model = TRUE,
mixed_model = TRUE,
n_obs = 500L,
model_class = "lqmm",
bootstrap = FALSE,
iterations = 1000,
ignore_group = TRUE,
ran_pars = TRUE,
weighted_nobs = 500,
model_formula = "y ~ x",
coefficient_name = "Coefficient",
zi_coefficient_name = "Log-Odds",
digits = 2,
ci_digits = 2,
p_digits = 3,
class = "data.frame",
object_name = "fit.lqmm"
),
tolerance = 0.001
)
})
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