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authorJohannes Ranke <jranke@uni-bremen.de>2022-10-05 08:10:43 +0200
committerJohannes Ranke <jranke@uni-bremen.de>2022-10-05 08:10:43 +0200
commite7e8105390ebf3d6f034811bc7cce1d9640b7357 (patch)
tree55f79edc01f86530c65eec012b70e6ece205b4db /tests
parent3d0d6af9f87c23ca3e223a21c892c97fe95d346a (diff)
Simplify the removal of random effects
This is achieved by introducing the argument 'no_random_effect' to the saem function.
Diffstat (limited to 'tests')
-rw-r--r--tests/testthat/test_saemix_parent.R52
1 files changed, 38 insertions, 14 deletions
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")

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