diff options
Diffstat (limited to 'tests/testthat/test_mixed.R')
-rw-r--r-- | tests/testthat/test_mixed.R | 93 |
1 files changed, 1 insertions, 92 deletions
diff --git a/tests/testthat/test_mixed.R b/tests/testthat/test_mixed.R index 40bd3fdf..dbcc66ce 100644 --- a/tests/testthat/test_mixed.R +++ b/tests/testthat/test_mixed.R @@ -1,96 +1,5 @@ context("Nonlinear mixed-effects models") -test_that("Parent fits using saemix are correctly implemented", { - - expect_error(saem(fits), "Only row objects") - # Some fits were done in the setup script - mmkin_sfo_2 <- update(mmkin_sfo_1, fixed_initials = c(parent = 100)) - expect_error(update(mmkin_sfo_1, models = c("SFOOO")), "Please supply models.*") - - sfo_saem_2 <- saem(mmkin_sfo_1, quiet = TRUE, transformations = "mkin") - sfo_saem_3 <- expect_error(saem(mmkin_sfo_2, quiet = TRUE), "at least two parameters") - s_sfo_s1 <- summary(sfo_saem_1) - s_sfo_s2 <- summary(sfo_saem_2) - - sfo_nlme_1 <- expect_warning(nlme(mmkin_sfo_1), "not converge") - s_sfo_n <- summary(sfo_nlme_1) - - # Compare with input - expect_equal(round(s_sfo_s2$confint_ranef["SD.log_k_parent", "est."], 1), 0.3) - # k_parent is a bit different from input 0.03 here - expect_equal(round(s_sfo_s1$confint_back["k_parent", "est."], 3), 0.035) - expect_equal(round(s_sfo_s2$confint_back["k_parent", "est."], 3), 0.035) - - # But the result is pretty unanimous between methods - expect_equal(round(s_sfo_s1$confint_back["k_parent", "est."], 3), - round(s_sfo_s2$confint_back["k_parent", "est."], 3)) - expect_equal(round(s_sfo_s1$confint_back["k_parent", "est."], 3), - round(s_sfo_n$confint_back["k_parent", "est."], 3)) - - mmkin_fomc_1 <- mmkin("FOMC", ds_fomc, quiet = TRUE, error_model = "tc", cores = n_cores) - fomc_saem_1 <- saem(mmkin_fomc_1, quiet = TRUE) - ci_fomc_s1 <- summary(fomc_saem_1)$confint_back - - fomc_pop <- as.numeric(fomc_pop) - expect_true(all(ci_fomc_s1[, "lower"] < fomc_pop)) - expect_true(all(ci_fomc_s1[, "upper"] > fomc_pop)) - - mmkin_fomc_2 <- update(mmkin_fomc_1, state.ini = 100, fixed_initials = "parent") - fomc_saem_2 <- saem(mmkin_fomc_2, quiet = TRUE, transformations = "mkin") - ci_fomc_s2 <- summary(fomc_saem_2)$confint_back - - expect_true(all(ci_fomc_s2[, "lower"] < fomc_pop[2:3])) - expect_true(all(ci_fomc_s2[, "upper"] > fomc_pop[2:3])) - - s_dfop_s1 <- summary(dfop_saemix_1) - s_dfop_s2 <- summary(dfop_saemix_2) - s_dfop_n <- summary(dfop_nlme_1) - - dfop_pop <- as.numeric(dfop_pop) - expect_true(all(s_dfop_s1$confint_back[, "lower"] < dfop_pop)) - expect_true(all(s_dfop_s1$confint_back[, "upper"] > dfop_pop)) - expect_true(all(s_dfop_s2$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$mkinmod) - - # We get < 20% deviations for parent_0 and k1 by averaging the transformed parameters - # If we average only parameters passing the t-test, the deviation for k2 is also < 20% - rel_diff_mmkin <- (dfop_mmkin_means - dfop_pop) / dfop_pop - rel_diff_mmkin_tested <- (dfop_mmkin_means_tested - dfop_pop) / dfop_pop - expect_true(all(rel_diff_mmkin[c("parent_0", "k1")] < 0.20)) - expect_true(all(rel_diff_mmkin_tested[c("parent_0", "k1", "k2")] < 0.20)) - - # We get < 15% deviations with transformations made in mkin - rel_diff_1 <- (s_dfop_s1$confint_back[, "est."] - dfop_pop) / dfop_pop - expect_true(all(rel_diff_1 < 0.15)) - - # We get < 20% deviations with transformations made in saemix - rel_diff_2 <- (s_dfop_s2$confint_back[, "est."] - dfop_pop) / dfop_pop - expect_true(all(rel_diff_2 < 0.2)) - - mmkin_hs_1 <- mmkin("HS", ds_hs, quiet = TRUE, error_model = "const", cores = n_cores) - hs_saem_1 <- saem(mmkin_hs_1, quiet = TRUE) - ci_hs_s1 <- summary(hs_saem_1)$confint_back - - hs_pop <- as.numeric(hs_pop) - # expect_true(all(ci_hs_s1[, "lower"] < hs_pop)) # k1 is overestimated - expect_true(all(ci_hs_s1[, "upper"] > hs_pop)) - - mmkin_hs_2 <- update(mmkin_hs_1, state.ini = 100, fixed_initials = "parent") - hs_saem_2 <- saem(mmkin_hs_2, quiet = TRUE) - ci_hs_s2 <- summary(hs_saem_2)$confint_back - - #expect_true(all(ci_hs_s2[, "lower"] < hs_pop[2:4])) # k1 again overestimated - expect_true(all(ci_hs_s2[, "upper"] > hs_pop[2:4])) - - # HS would likely benefit from implemenation of transformations = "saemix" -}) - test_that("Print methods work", { expect_known_output(print(fits[, 2:3], digits = 2), "print_mmkin_parent.txt") expect_known_output(print(mmkin_biphasic_mixed, digits = 2), "print_mmkin_biphasic_mixed.txt") @@ -122,7 +31,7 @@ test_that("nlme results are reproducible to some degree", { expect_true(all(ci_dfop_sfo_n[, "upper"] > dfop_sfo_pop)) }) -test_that("saem results are reproducible for biphasic fits", { +test_that("saemix results are reproducible for biphasic fits", { test_summary <- summary(saem_biphasic_s) test_summary$saemixversion <- "Dummy 0.0 for testing" |