.runThisTest <- Sys.getenv("RunAllinsightTests") == "yes" if (.runThisTest && requiet("mmrm") && getRversion() >= "4.0.0") { data(fev_data) m1 <- mmrm( formula = FEV1 ~ RACE + SEX + ARMCD * AVISIT + us(AVISIT | USUBJID), data = fev_data ) test_that("model_info", { expect_true(model_info(m1)$is_linear) expect_true(model_info(m1)$is_mixed) }) test_that("loglik", { expect_equal(get_loglikelihood(m1, estimator = "REML"), logLik(m1), ignore_attr = TRUE) expect_equal(get_loglikelihood(m1), logLik(m1), ignore_attr = TRUE) }) test_that("get_df", { expect_equal(get_df(m1), c( 218.8018, 168.6657, 157.1382, 166.1324, 145.552, 143.8758, 155.5575, 138.4708, 138.5643, 158.1651, 129.7204 ), ignore_attr = TRUE, tolerance = 1e-4) expect_equal(get_df(m1, type = "model"), 12, ignore_attr = TRUE) }) test_that("n_parameters", { expect_identical(n_parameters(m1), 11L) }) test_that("find_offset", { model_off <- mmrm(log(FEV1) ~ RACE + SEX + ARMCD * AVISIT + us(AVISIT | USUBJID) + offset(log(FEV1_BL)), data = fev_data) expect_identical(find_offset(model_off), "FEV1_BL") }) test_that("find_predictors", { expect_identical( find_predictors(m1, effects = "all"), list(conditional = c("RACE", "SEX", "ARMCD", "AVISIT"), random = "USUBJID") ) expect_identical( find_predictors(m1, effects = "all", flatten = TRUE), c("RACE", "SEX", "ARMCD", "AVISIT", "USUBJID") ) expect_identical( find_predictors(m1, effects = "fixed"), list(conditional = c("RACE", "SEX", "ARMCD", "AVISIT")) ) expect_identical( find_predictors(m1, effects = "fixed", flatten = TRUE), c("RACE", "SEX", "ARMCD", "AVISIT") ) expect_identical( find_predictors(m1, effects = "random"), list(random = "USUBJID") ) expect_identical( find_predictors(m1, effects = "random", flatten = TRUE), "USUBJID" ) expect_null(find_predictors(m1, effects = "all", component = "zi")) }) test_that("find_random", { expect_identical(find_random(m1), list(random = "USUBJID")) expect_identical(find_random(m1, flatten = TRUE), "USUBJID") }) test_that("find_response", { expect_identical(find_response(m1), "FEV1") }) test_that("get_response", { expect_equal(get_response(m1), na.omit(fev_data$FEV1), ignore_attr = TRUE, tolerance = 1e-4) }) test_that("link_inverse", { expect_identical(link_inverse(m1)(0.2), 0.2) }) test_that("get_data", { expect_identical(colnames(get_data(m1)), c("FEV1", "RACE", "SEX", "ARMCD", "AVISIT", "USUBJID")) expect_identical(colnames(get_data(m1, effects = "fixed")), c("FEV1", "RACE", "SEX", "ARMCD", "AVISIT")) expect_identical(colnames(get_data(m1, effects = "random")), "USUBJID") expect_identical(dim(get_data(m1)), c(537L, 6L)) }) test_that("find_formula", { expect_length(find_formula(m1), 2) expect_equal( find_formula(m1, component = "conditional"), list( conditional = as.formula("FEV1 ~ RACE + SEX + ARMCD * AVISIT"), random = as.formula("~AVISIT | USUBJID") ), ignore_attr = TRUE ) }) test_that("find_terms", { expect_identical( find_terms(m1), list(response = "FEV1", conditional = c( "RACE", "SEX", "ARMCD", "AVISIT" ), random = c("AVISIT", "USUBJID")) ) expect_identical( find_terms(m1, flatten = TRUE), c("FEV1", "RACE", "SEX", "ARMCD", "AVISIT", "USUBJID") ) }) test_that("get_predictors", { expect_identical(colnames(get_predictors(m1)), c("RACE", "SEX", "ARMCD", "AVISIT")) }) test_that("get_random", { expect_identical(colnames(get_random(m1)), "USUBJID") }) test_that("linkfun", { expect_false(is.null(link_function(m1))) }) test_that("find_parameters", { expect_identical( find_parameters(m1), list(conditional = c( "(Intercept)", "RACEBlack or African American", "RACEWhite", "SEXFemale", "ARMCDTRT", "AVISITVIS2", "AVISITVIS3", "AVISITVIS4", "ARMCDTRT:AVISITVIS2", "ARMCDTRT:AVISITVIS3", "ARMCDTRT:AVISITVIS4" )) ) expect_identical(nrow(get_parameters(m1)), 11L) expect_identical( get_parameters(m1)$Parameter, c( "(Intercept)", "RACEBlack or African American", "RACEWhite", "SEXFemale", "ARMCDTRT", "AVISITVIS2", "AVISITVIS3", "AVISITVIS4", "ARMCDTRT:AVISITVIS2", "ARMCDTRT:AVISITVIS3", "ARMCDTRT:AVISITVIS4" ) ) }) test_that("is_multivariate", { expect_false(is_multivariate(m1)) }) test_that("find_random_slopes", { expect_identical(find_random_slopes(m1), list(random = "AVISIT")) }) test_that("get_varcov", { expect_identical(dim(get_varcov(m1)), c(11L, 11L)) }) test_that("find_statistic", { expect_identical(find_statistic(m1), "t-statistic") }) }
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