# 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 ) })