diff options
Diffstat (limited to 'tests/testthat/test_saemix_parent.R')
| -rw-r--r-- | tests/testthat/test_saemix_parent.R | 56 |
1 files changed, 29 insertions, 27 deletions
diff --git a/tests/testthat/test_saemix_parent.R b/tests/testthat/test_saemix_parent.R index 39f69f51..4504e573 100644 --- a/tests/testthat/test_saemix_parent.R +++ b/tests/testthat/test_saemix_parent.R @@ -5,6 +5,7 @@ test_that("Parent fits using saemix are correctly implemented", { skip_on_cran() expect_error(saem(fits), "Only row objects") + # SFO # mmkin_sfo_1 was generated in the setup script # We did not introduce variance of parent_0 in the data generation # This is correctly detected @@ -53,9 +54,16 @@ test_that("Parent fits using saemix are correctly implemented", { expect_equal(round(s_sfo_nlme_1$confint_back["k_parent", "est."], 3), round(s_sfo_saem_1$confint_back["k_parent", "est."], 3)) + # Compare fits + expect_known_output(anova(sfo_saem_1, sfo_saem_1_reduced, + sfo_saem_1_mkin, sfo_saem_1_reduced_mkin, test = TRUE), + file = "anova_sfo_saem.txt" + ) + + # FOMC mmkin_fomc_1 <- mmkin("FOMC", ds_fomc, quiet = TRUE, error_model = "tc", cores = n_cores) - fomc_saem_1 <- saem(mmkin_fomc_1, quiet = TRUE, transformations = "saemix") - fomc_saem_2 <- saem(mmkin_fomc_1, quiet = TRUE, transformations = "mkin") + fomc_saem_1 <- saem(mmkin_fomc_1, quiet = TRUE, transformations = "saemix", no_random_effect = "parent_0") + fomc_saem_2 <- update(fomc_saem_1, transformations = "mkin") ci_fomc_s1 <- summary(fomc_saem_1)$confint_back fomc_pop <- as.numeric(fomc_pop) @@ -70,45 +78,39 @@ test_that("Parent fits using saemix are correctly implemented", { expect_true(all(ci_fomc_s2[, "lower"] < fomc_pop[2:3])) expect_true(all(ci_fomc_s2[, "upper"] > fomc_pop[2:3])) + # DFOP + dfop_saemix_2 <- saem(mmkin_dfop_1, quiet = TRUE, transformations = "saemix", + no_random_effect = "parent_0") + s_dfop_s1 <- summary(dfop_saemix_1) s_dfop_s2 <- summary(dfop_saemix_2) s_dfop_n <- summary(dfop_nlme_1) dfop_pop <- as.numeric(dfop_pop) - expect_true(all(s_dfop_s1$confint_back[, "lower"] < dfop_pop)) - expect_true(all(s_dfop_s1$confint_back[, "upper"] > dfop_pop)) + + # When using DFOP with mkin transformations, k1 and k2 are sometimes swapped + swap_k1_k2 <- function(p) c(p[1], p[3], p[2], 1 - p[4]) + expect_true(all(s_dfop_s1$confint_back[, "lower"] < swap_k1_k2(dfop_pop))) + expect_true(all(s_dfop_s1$confint_back[, "upper"] > swap_k1_k2(dfop_pop))) expect_true(all(s_dfop_s2$confint_back[, "lower"] < dfop_pop)) expect_true(all(s_dfop_s2$confint_back[, "upper"] > dfop_pop)) - dfop_mmkin_means_trans_tested <- mean_degparms(mmkin_dfop_1, test_log_parms = TRUE) - dfop_mmkin_means_trans <- apply(parms(mmkin_dfop_1, transformed = TRUE), 1, mean) - - dfop_mmkin_means_tested <- backtransform_odeparms(dfop_mmkin_means_trans_tested, mmkin_dfop_1$mkinmod) - dfop_mmkin_means <- backtransform_odeparms(dfop_mmkin_means_trans, mmkin_dfop_1$mkinmod) - - # We get < 20% deviations for parent_0 and k1 by averaging the transformed parameters - # If we average only parameters passing the t-test, the deviation for k2 is also < 20% - rel_diff_mmkin <- (dfop_mmkin_means - dfop_pop) / dfop_pop - rel_diff_mmkin_tested <- (dfop_mmkin_means_tested - dfop_pop) / dfop_pop - expect_true(all(rel_diff_mmkin[c("parent_0", "k1")] < 0.20)) - expect_true(all(rel_diff_mmkin_tested[c("parent_0", "k1", "k2")] < 0.20)) - - # We get < 20% deviations with transformations made in mkin - rel_diff_1 <- (s_dfop_s1$confint_back[, "est."] - dfop_pop) / dfop_pop + # We get < 20% deviations with transformations made in mkin (need to swap k1 and k2) + rel_diff_1 <- (swap_k1_k2(s_dfop_s1$confint_back[, "est."]) - dfop_pop) / dfop_pop expect_true(all(rel_diff_1 < 0.20)) # We get < 20% deviations with transformations made in saemix rel_diff_2 <- (s_dfop_s2$confint_back[, "est."] - dfop_pop) / dfop_pop expect_true(all(rel_diff_2 < 0.2)) - # We use constant error for SFORB because tc is overparameterised (b.1 is ill-defined in saem) - mmkin_sforb_2 <- mmkin("SFORB", ds_dfop, quiet = TRUE, error_model = "const", cores = n_cores) - sforb_saemix_1 <- saem(mmkin_sforb_2, quiet = TRUE, - no_random_effect = c("parent_free_0", "k_parent_free_bound"), - transformations = "saemix") - sforb_saemix_2 <- saem(mmkin_sforb_2, quiet = TRUE, - no_random_effect = c("parent_free_0", "log_k_parent_free_bound"), + # SFORB + mmkin_sforb_1 <- mmkin("SFORB", ds_dfop, quiet = TRUE, cores = n_cores) + sforb_saemix_1 <- saem(mmkin_sforb_1, quiet = TRUE, + no_random_effect = c("parent_free_0"), transformations = "mkin") + sforb_saemix_2 <- saem(mmkin_sforb_1, quiet = TRUE, + no_random_effect = c("parent_free_0"), + transformations = "saemix") expect_equal( log(endpoints(dfop_saemix_1)$distimes[1:2]), log(endpoints(sforb_saemix_1)$distimes[1:2]), tolerance = 0.03) @@ -140,7 +142,7 @@ test_that("We can also use mkin solution methods for saem", { ) skip_on_cran() # This still takes almost 2.5 minutes although we do not solve ODEs dfop_saemix_3 <- saem(mmkin_dfop_1, quiet = TRUE, transformations = "mkin", - solution_type = "analytical") + solution_type = "analytical", no_random_effect = "parent_0") distimes_dfop <- endpoints(dfop_saemix_1)$distimes distimes_dfop_analytical <- endpoints(dfop_saemix_3)$distimes rel_diff <- abs(distimes_dfop_analytical - distimes_dfop) / distimes_dfop |