#------------------------------------------------------------------------------- # Copyright (c) 2019-2022 University of Newcastle upon Tyne. All rights reserved. # # This program and the accompanying materials # are made available under the terms of the GNU Public License v3.0. # # You should have received a copy of the GNU General Public License # along with this program. If not, see . #------------------------------------------------------------------------------- # # Set up # context("ds.glmerSLMA::arg::setup") connect.studies.dataset.cluster.int(list("incid_rate", "trtGrp", "Male", "idDoctor", "idSurgery")) test_that("setup", { ds_expect_variables(c("D")) }) # # Test # context("ds.glmerSLMA::arg::testing") test_that("simple glmerSLMA tesing (mis)use of arguments", { expect_error(ds.glmerSLMA(formula = 'incid_rate ~ trtGrp + Male + (1|idDoctor)', dataName = 'D'), " Please provide a valid 'family' argument!", fixed=TRUE) expect_error(ds.glmerSLMA(formula = 'diab_dis ~ trtGrp + Male + (1|idDoctor)', family='poisson', dataName = 'D'), "There are some DataSHIELD errors, list them with datashield.errors()", fixed=TRUE) errs <- datashield.errors() expect_length(errs, 3) expect_length(errs$sim1, 0) expect_length(errs$sim2, 0) expect_length(errs$sim3, 0) res <- ds.glmerSLMA(formula = 'incid_rate ~ trtGrp + Male + (1|idDoctor)', family='poisson', dataName = 'D', control_type = 'xtol_rel') expect_equal(res$errorMessage, "ERROR: if control_type is non-null, you must specify a valid control_value eg control_value<-1.0e-7",fixed=TRUE) expect_error(ds.glmerSLMA(formula = 'incid_rate ~ trtGrp + Male + (1|idDoctor)', family='poisson', dataName = 'D', control_type = 'check.conv.grad',control_value = 'nothing'), "There are some DataSHIELD errors, list them with datashield.errors()", fixed=TRUE) errs <- datashield.errors() expect_length(errs, 3) expect_length(errs$sim1, 0) expect_length(errs$sim2, 0) expect_length(errs$sim3, 0) expect_error(ds.glmerSLMA(), " Please provide a valid regression formula!", fixed=TRUE) }) # # Shutdown # context("ds.glmerSLMA::arg::shutdown") test_that("setup", { ds_expect_variables(c("D", "offset", "weights")) }) disconnect.studies.dataset.cluster.int() # # Done # context("ds.glmerSLMA::arg::done")