context("Nonlinear mixed-effects models") # Round error model parameters as they are not rounded in print methods dfop_nlme_1$modelStruct$varStruct$const <- signif(dfop_nlme_1$modelStruct$varStruct$const, 3) dfop_nlme_1$modelStruct$varStruct$prop <- signif(dfop_nlme_1$modelStruct$varStruct$prop, 4) dfop_sfo_pop <- attr(ds_dfop_sfo, "pop") test_that("Print methods work", { expect_known_output(print(fits[, 2:3], digits = 2), "print_mmkin_parent.txt") expect_known_output(print(mixed(mmkin_sfo_1), digits = 2), "print_mmkin_sfo_1_mixed.txt") expect_known_output(print(dfop_nlme_1, digits = 1), "print_dfop_nlme_1.txt") expect_known_output(print(sfo_saem_1_reduced, digits = 1), "print_sfo_saem_1_reduced.txt") skip_on_cran() # The following test is platform dependent and fails on # win-builder with current (18 Nov 2022) R-devel, on the Linux R-devel CRAN check systems # and also using R-devel locally expect_known_output(print(dfop_saem_1, digits = 1), "print_dfop_saem_1.txt") }) test_that("nlme results are reproducible to some degree", { test_summary <- summary(dfop_nlme_1) test_summary$nlmeversion <- "Dummy 0.0 for testing" test_summary$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 = 1), "summary_dfop_nlme_1.txt") # The biphasic example data illustrate that DFOP parameters are difficult to # quantify with the usual design # k1 and k2 just fail the first test (lower bound of the ci), so we need to exclude it dfop_no_k1_k2 <- c("parent_0", "k_m1", "f_parent_to_m1", "g") dfop_sfo_pop_no_k1_k2 <- as.numeric(dfop_sfo_pop[dfop_no_k1_k2]) ci_dfop_sfo_n <- summary(nlme_dfop_sfo)$confint_back expect_true(all(ci_dfop_sfo_n[dfop_no_k1_k2, "lower"] < dfop_sfo_pop_no_k1_k2)) expect_true(all(ci_dfop_sfo_n[, "upper"] > as.numeric(dfop_sfo_pop))) }) test_that("saemix results are reproducible for biphasic fits", { skip_on_cran() saem_dfop_sfo_s <- saem(mmkin_dfop_sfo, transformations = "saemix", quiet = TRUE) test_summary <- summary(saem_dfop_sfo_s) test_summary$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$time <- c(elapsed = "test time 0") expect_known_output(print(test_summary, digits = 1), "summary_saem_dfop_sfo_s.txt") dfop_sfo_pop <- as.numeric(dfop_sfo_pop) no_k1 <- c(1, 2, 3, 5, 6) no_k2 <- c(1, 2, 3, 4, 6) no_k1_k2 <- c(1, 2, 3, 6) ci_dfop_sfo_s_s <- summary(saem_dfop_sfo_s)$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)) # 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_dfop_sfo_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_dfop_sfo_2 <- saem(mmkin_dfop_sfo, solution_type = "deSolve", quiet = TRUE) # As with the analytical solution, k1 and k2 are not fitted well ci_dfop_sfo_s_d <- summary(saem_dfop_sfo_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])) })