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Diffstat (limited to 'tests/testthat/test_dmta.R')
-rw-r--r-- | tests/testthat/test_dmta.R | 120 |
1 files changed, 120 insertions, 0 deletions
diff --git a/tests/testthat/test_dmta.R b/tests/testthat/test_dmta.R new file mode 100644 index 00000000..3437966f --- /dev/null +++ b/tests/testthat/test_dmta.R @@ -0,0 +1,120 @@ +context("Dimethenamid data from 2018, parent fits") + +# Data +dmta_ds <- lapply(1:7, function(i) { + ds_i <- dimethenamid_2018$ds[[i]]$data + ds_i[ds_i$name == "DMTAP", "name"] <- "DMTA" + ds_i$time <- ds_i$time * dimethenamid_2018$f_time_norm[i] + ds_i +}) +names(dmta_ds) <- sapply(dimethenamid_2018$ds, function(ds) ds$title) +dmta_ds[["Elliot"]] <- rbind(dmta_ds[["Elliot 1"]], dmta_ds[["Elliot 2"]]) +dmta_ds[["Elliot 1"]] <- dmta_ds[["Elliot 2"]] <- NULL + +# mkin +dmta_dfop <- mmkin("DFOP", dmta_ds, quiet = TRUE) +dmta_dfop_tc <- mmkin("DFOP", dmta_ds, error_model = "tc", quiet = TRUE) + +test_that("Different backends get consistent results for DFOP tc, dimethenamid data", { + + # nlme + expect_warning( + nlme_dfop_tc <- nlme(dmta_dfop_tc), + "Iteration 3, .* false convergence") + ints_nlme <- intervals(nlme_dfop_tc) + + # saemix + saem_saemix_dfop_tc <- saem(dmta_dfop_tc) + ints_saemix <- intervals(saem_saemix_dfop_tc) + + # saemix mkin transformations + saem_saemix_dfop_tc_mkin <- saem(dmta_dfop_tc, transformations = "mkin") + ints_saemix_mkin <- intervals(saem_saemix_dfop_tc_mkin) + + # nlmixr saem + saem_nlmixr_dfop_tc <- nlmixr(dmta_dfop_tc, est = "saem", + control = nlmixr::saemControl(nBurn = 300, nEm = 100, nmc = 9, print = 0)) + ints_nlmixr_saem <- intervals(saem_nlmixr_dfop_tc) + + # nlmixr focei + # We get three warnings about nudged etas, the initial optimization and + # gradient problems with initial estimate and covariance + # We need to capture output, otherwise it pops up in testthat output + expect_warning(tmp <- capture_output(focei_nlmixr_dfop_tc <- nlmixr( + dmta_dfop_tc, est = "focei", + control = nlmixr::foceiControl(print = 0), all = TRUE))) + ints_nlmixr_focei <- intervals(focei_nlmixr_dfop_tc) + + # Fixed effects + ## saemix vs. nlme + expect_true(all(ints_saemix$fixed[, "est."] > + backtransform_odeparms(ints_nlme$fixed[, "lower"], dmta_dfop$mkinmod))) + expect_true(all(ints_saemix$fixed[, "est."] < + backtransform_odeparms(ints_nlme$fixed[, "upper"], dmta_dfop$mkinmod))) + + ## saemix mkin vs. nlme + expect_true(all(ints_saemix_mkin$fixed[, "est."] > + backtransform_odeparms(ints_nlme$fixed[, "lower"], dmta_dfop$mkinmod))) + expect_true(all(ints_saemix_mkin$fixed[, "est."] < + backtransform_odeparms(ints_nlme$fixed[, "upper"], dmta_dfop$mkinmod))) + + ## nlmixr saem vs. nlme + expect_true(all(ints_nlmixr_saem$fixed[, "est."] > + backtransform_odeparms(ints_nlme$fixed[, "lower"], dmta_dfop$mkinmod))) + expect_true(all(ints_nlmixr_saem$fixed[, "est."] < + backtransform_odeparms(ints_nlme$fixed[, "upper"], dmta_dfop$mkinmod))) + + ## nlmixr focei vs. nlme + expect_true(all(ints_nlmixr_focei$fixed[, "est."] > + backtransform_odeparms(ints_nlme$fixed[, "lower"], dmta_dfop$mkinmod))) + expect_true(all(ints_nlmixr_focei$fixed[, "est."] < + backtransform_odeparms(ints_nlme$fixed[, "upper"], dmta_dfop$mkinmod))) + + # Random effects + ## for saemix with saemix transformations, the comparison would be complicated... + ## saemix mkin vs. nlme + expect_true(all(ints_saemix$random[, "est."] > + backtransform_odeparms(ints_nlme$reStruct$ds[, "lower"], dmta_dfop$mkinmod))) + expect_true(all(ints_saemix$fixed[, "est."] < + backtransform_odeparms(ints_nlme$fixed[, "upper"], dmta_dfop$mkinmod))) + + ## nlmixr saem vs. nlme + expect_true(all(ints_nlmixr_saem$random[, "est."] > + backtransform_odeparms(ints_nlme$reStruct$ds[, "lower"], dmta_dfop$mkinmod))) + expect_true(all(ints_nlmixr_saem$random[, "est."] < + backtransform_odeparms(ints_nlme$reStruct$ds[, "upper"], dmta_dfop$mkinmod))) + + ## nlmixr focei vs. nlme + expect_true(all(ints_nlmixr_focei$random[, "est."] > + backtransform_odeparms(ints_nlme$reStruct$ds[, "lower"], dmta_dfop$mkinmod))) + expect_true(all(ints_nlmixr_focei$random[, "est."] < + backtransform_odeparms(ints_nlme$reStruct$ds[, "upper"], dmta_dfop$mkinmod))) + + # Variance function + # saemix vs. nlme + expect_true(all(ints_saemix[[3]][, "est."] > + ints_nlme$varStruct[, "lower"])) + expect_true(all(ints_saemix[[3]][, "est."] < + ints_nlme$varStruct[, "upper"])) + + # saemix with mkin transformations vs. nlme + expect_true(all(ints_saemix_mkin[[3]][, "est."] > + ints_nlme$varStruct[, "lower"])) + expect_true(all(ints_saemix_mkin[[3]][, "est."] < + ints_nlme$varStruct[, "upper"])) + + # nlmixr saem vs. nlme + expect_true(all(ints_nlmixr_saem[[3]][, "est."] > + ints_nlme$varStruct[, "lower"])) + expect_true(all(ints_nlmixr_saem[[3]][, "est."] < + ints_nlme$varStruct[, "upper"])) + + # nlmixr focei vs. nlme + # We only test for the proportional part (rsd_high), as the + # constant part (sigma_low) obtained with nlmixr/FOCEI is below the lower + # bound of the confidence interval obtained with nlme + expect_true(ints_nlmixr_focei[[3]]["rsd_high", "est."] > + ints_nlme$varStruct["prop", "lower"]) + expect_true(ints_nlmixr_focei[[3]]["rsd_high", "est."] < + ints_nlme$varStruct["prop", "upper"]) +}) |