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Diffstat (limited to 'tests/testthat/test_mixed.R')
-rw-r--r-- | tests/testthat/test_mixed.R | 131 |
1 files changed, 0 insertions, 131 deletions
diff --git a/tests/testthat/test_mixed.R b/tests/testthat/test_mixed.R index e9af10e6..ca0072ef 100644 --- a/tests/testthat/test_mixed.R +++ b/tests/testthat/test_mixed.R @@ -1,98 +1,9 @@ context("Nonlinear mixed-effects models") -test_that("Parent fits using saemix are correctly implemented", { - skip_if(!saemix_available) - - 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$confint_back[, "upper"] > dfop_pop)) - - dfop_mmkin_means_trans <- apply(parms(mmkin_dfop_1, transformed = TRUE), 1, mean) - dfop_mmkin_means <- backtransform_odeparms(dfop_mmkin_means_trans, mmkin_dfop_1$mkinmod) - - # We get < 22% deviations by averaging the transformed parameters - rel_diff_mmkin <- (dfop_mmkin_means - dfop_pop) / dfop_pop - expect_true(all(rel_diff_mmkin < 0.22)) - - # We get < 50% deviations with transformations made in mkin - rel_diff_1 <- (s_dfop_s1$confint_back[, "est."] - dfop_pop) / dfop_pop - expect_true(all(rel_diff_1 < 0.5)) - - # We get < 12% deviations with transformations made in saemix - rel_diff_2 <- (s_dfop_s2$confint_back[, "est."] - dfop_pop) / dfop_pop - expect_true(all(rel_diff_2 < 0.12)) - - 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, digits = 2), "print_mmkin_parent.txt") expect_known_output(print(mmkin_biphasic_mixed, digits = 2), "print_mmkin_biphasic_mixed.txt") expect_known_output(print(nlme_biphasic, digits = 1), "print_nlme_biphasic.txt") - - skip_if(!saemix_available) - expect_known_output(print(sfo_saem_1, digits = 1), "print_sfo_saem_1.txt") }) test_that("nlme results are reproducible to some degree", { @@ -112,45 +23,3 @@ test_that("nlme results are reproducible to some degree", { # expect_true(all(ci_dfop_sfo_n[, "lower"] < dfop_sfo_pop)) # k2 is overestimated expect_true(all(ci_dfop_sfo_n[, "upper"] > dfop_sfo_pop)) }) - -test_that("saem results are reproducible for biphasic fits", { - - skip_if(!saemix_available) - test_summary <- summary(saem_biphasic_s) - test_summary$saemixversion <- "Dummy 0.0 for testing" - test_summary$mkinversion <- "Dummy 0.0 for testing" - test_summary$Rversion <- "Dummy R version for testing" - test_summary$date.fit <- "Dummy date for testing" - test_summary$date.summary <- "Dummy date for testing" - test_summary$time <- c(elapsed = "test time 0") - - expect_known_output(print(test_summary, digits = 2), "summary_saem_biphasic_s.txt") - - dfop_sfo_pop <- as.numeric(dfop_sfo_pop) - no_k1 <- c(1, 2, 3, 5, 6) - no_k2 <- c(1, 2, 3, 4, 6) - - ci_dfop_sfo_s_s <- summary(saem_biphasic_s)$confint_back - expect_true(all(ci_dfop_sfo_s_s[, "lower"] < dfop_sfo_pop)) - expect_true(all(ci_dfop_sfo_s_s[, "upper"] > dfop_sfo_pop)) - - # k1 and k2 are not fitted well - ci_dfop_sfo_s_m <- summary(saem_biphasic_m)$confint_back - expect_true(all(ci_dfop_sfo_s_m[no_k2, "lower"] < dfop_sfo_pop[no_k2])) - expect_true(all(ci_dfop_sfo_s_m[no_k1, "upper"] > dfop_sfo_pop[no_k1])) - - # I tried to only do few iterations in routine tests as this is so slow - # but then deSolve fails at some point (presumably at the switch between - # the two types of iterations) - #saem_biphasic_2 <- saem(mmkin_biphasic, solution_type = "deSolve", - # control = list(nbiter.saemix = c(10, 5), nbiter.burn = 5), quiet = TRUE) - - skip("Fitting with saemix takes around 10 minutes when using deSolve") - saem_biphasic_2 <- saem(mmkin_biphasic, solution_type = "deSolve", quiet = TRUE) - - # As with the analytical solution, k1 and k2 are not fitted well - ci_dfop_sfo_s_d <- summary(saem_biphasic_2)$confint_back - expect_true(all(ci_dfop_sfo_s_d[no_k2, "lower"] < dfop_sfo_pop[no_k2])) - expect_true(all(ci_dfop_sfo_s_d[no_k1, "upper"] > dfop_sfo_pop[no_k1])) -}) - |