From e7e8105390ebf3d6f034811bc7cce1d9640b7357 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Wed, 5 Oct 2022 08:10:43 +0200 Subject: Simplify the removal of random effects This is achieved by introducing the argument 'no_random_effect' to the saem function. --- tests/testthat/test_saemix_parent.R | 52 +++++++++++++++++++++++++++---------- 1 file changed, 38 insertions(+), 14 deletions(-) (limited to 'tests') diff --git a/tests/testthat/test_saemix_parent.R b/tests/testthat/test_saemix_parent.R index 5d9a01de..ce776bf7 100644 --- a/tests/testthat/test_saemix_parent.R +++ b/tests/testthat/test_saemix_parent.R @@ -4,30 +4,54 @@ test_that("Parent fits using saemix are correctly implemented", { skip_on_cran() expect_error(saem(fits), "Only row objects") - # Some fits were done in the setup script + + # 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 + expect_equal(illparms(sfo_saem_1), "sd(parent_0)") + # So we remove this variance + sfo_saem_1_reduced <- update(sfo_saem_1, no_random_effect = "parent_0") + expect_equal(illparms(sfo_saem_1_reduced), character(0)) + + # We cannot currently do the fit with completely fixed initial values mmkin_sfo_2 <- update(mmkin_sfo_1, fixed_initials = c(parent = 100)) + sfo_saem_3 <- expect_error(saem(mmkin_sfo_2, quiet = TRUE), "at least two parameters") + + # We get an error if we do not supply a suitable model specification 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") - expect_equal(endpoints(sfo_saem_1), endpoints(sfo_saem_2), tol = 0.01) - s_sfo_s1 <- summary(sfo_saem_1) - s_sfo_s2 <- summary(sfo_saem_2) + sfo_saem_1_mkin <- saem(mmkin_sfo_1, quiet = TRUE, transformations = "mkin") + expect_equal(illparms(sfo_saem_1_mkin), "sd(parent_0)") + sfo_saem_1_reduced_mkin <- update(sfo_saem_1_mkin, no_random_effect = "parent_0") + + # The endpoints obtained do not depend on the transformation + expect_equal(endpoints(sfo_saem_1), endpoints(sfo_saem_1_mkin), tol = 0.01) + expect_equal(endpoints(sfo_saem_1_reduced), endpoints(sfo_saem_1_reduced_mkin), tol = 0.01) + + s_sfo_saem_1 <- summary(sfo_saem_1) + s_sfo_saem_1_reduced <- summary(sfo_saem_1_reduced) + s_sfo_saem_1_mkin <- summary(sfo_saem_1_mkin) + s_sfo_saem_1_reduced_mkin <- summary(sfo_saem_1_reduced_mkin) sfo_nlme_1 <- expect_warning(nlme(mmkin_sfo_1), "not converge") - s_sfo_n <- summary(sfo_nlme_1) + s_sfo_nlme_1 <- summary(sfo_nlme_1) # Compare with input - expect_equal(round(s_sfo_s2$confint_ranef["SD.log_k_parent", "est."], 1), 0.3) + expect_equal(round(s_sfo_saem_1$confint_ranef["SD.k_parent", "est."], 1), 0.3) + expect_equal(round(s_sfo_saem_1_mkin$confint_ranef["SD.log_k_parent", "est."], 1), 0.3) # k_parent is a bit different from input 0.03 here - expect_equal(round(s_sfo_s1$confint_back["k_parent", "est."], 3), 0.035) - expect_equal(round(s_sfo_s2$confint_back["k_parent", "est."], 3), 0.035) + expect_equal(round(s_sfo_saem_1$confint_back["k_parent", "est."], 3), 0.035) + expect_equal(round(s_sfo_saem_1_mkin$confint_back["k_parent", "est."], 3), 0.035) # But the result is pretty unanimous between methods - expect_equal(round(s_sfo_s1$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$confint_back["k_parent", "est."], 3)) + expect_equal(round(s_sfo_saem_1_reduced$confint_back["k_parent", "est."], 3), + round(s_sfo_saem_1$confint_back["k_parent", "est."], 3)) + expect_equal(round(s_sfo_saem_1_mkin$confint_back["k_parent", "est."], 3), + round(s_sfo_saem_1$confint_back["k_parent", "est."], 3)) + expect_equal(round(s_sfo_saem_1_reduced_mkin$confint_back["k_parent", "est."], 3), + round(s_sfo_saem_1$confint_back["k_parent", "est."], 3)) + expect_equal(round(s_sfo_nlme_1$confint_back["k_parent", "est."], 3), + round(s_sfo_saem_1$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, transformations = "saemix") -- cgit v1.2.1