#------------------------------------------------------------------------------- # 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.glmSLMA::smk::setup") connect.studies.dataset.cnsim(list("LAB_TSC", "LAB_TRIG", "MEDI_LPD", "DIS_AMI", "DIS_DIAB", "GENDER")) test_that("setup", { ds_expect_variables(c("D")) }) # # Tests # context("ds.glmSLMA::smk::gaussian") test_that("simple glmSLMA, gaussian", { glmSLMA.res <- ds.glmSLMA('D$LAB_TSC~D$LAB_TRIG', family="gaussian") expect_length(glmSLMA.res, 9) expect_equal(glmSLMA.res$num.valid.studies, 3) expect_true("matrix" %in% class(glmSLMA.res$betamatrix.all)) expect_true("matrix" %in% class(glmSLMA.res$sematrix.all)) expect_true("matrix" %in% class(glmSLMA.res$betamatrix.valid)) expect_true("matrix" %in% class(glmSLMA.res$sematrix.valid)) expect_true("matrix" %in% class(glmSLMA.res$SLMA.pooled.ests.matrix)) expect_length(glmSLMA.res$output.summary, 5) expect_true("matrix" %in% class(glmSLMA.res$output.summary$input.beta.matrix.for.SLMA)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$input.se.matrix.for.SLMA)) expect_length(glmSLMA.res$output.summary$study1, 29) expect_true("family" %in% class(glmSLMA.res$output.summary$study1$family)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$study1$coefficients)) expect_equal(glmSLMA.res$output.summary$study1$rank, 2) expect_equal(glmSLMA.res$output.summary$study1$aic, 5460.549, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study1$iter, 2) expect_equal(glmSLMA.res$output.summary$study1$contrasts, NULL) expect_equal(glmSLMA.res$output.summary$study1$dispersion, 1.211496, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study1$Ntotal, 2163) expect_equal(glmSLMA.res$output.summary$study1$Nvalid, 1801) expect_equal(glmSLMA.res$output.summary$study1$Nmissing, 362) expect_length(glmSLMA.res$output.summary$study2, 29) expect_true("family" %in% class(glmSLMA.res$output.summary$study2$family)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$study2$coefficients)) expect_equal(glmSLMA.res$output.summary$study2$rank, 2) expect_equal(glmSLMA.res$output.summary$study2$aic, 7490.000, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study2$iter, 2) expect_equal(glmSLMA.res$output.summary$study2$contrasts, NULL) expect_equal(glmSLMA.res$output.summary$study2$dispersion, 1.13414, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study2$Ntotal, 3088) expect_equal(glmSLMA.res$output.summary$study2$Nvalid, 2526) expect_equal(glmSLMA.res$output.summary$study2$Nmissing, 562) expect_length(glmSLMA.res$output.summary$study3, 29) expect_true("family" %in% class(glmSLMA.res$output.summary$study3$family)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$study3$coefficients)) expect_equal(glmSLMA.res$output.summary$study3$rank, 2) expect_equal(glmSLMA.res$output.summary$study3$aic, 10256.000, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study3$iter, 2) expect_equal(glmSLMA.res$output.summary$study3$contrasts, NULL) expect_equal(glmSLMA.res$output.summary$study3$dispersion, 1.12, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study3$Ntotal, 4128) expect_equal(glmSLMA.res$output.summary$study3$Nvalid, 3473) expect_equal(glmSLMA.res$output.summary$study3$Nmissing, 655) expect_length(glmSLMA.res$is.object.created, 1) expect_equal(glmSLMA.res$is.object.created, "A data object has been created in all specified data sources") expect_length(glmSLMA.res$validity.check, 1) expect_equal(glmSLMA.res$validity.check, " appears valid in all sources") }) context("ds.glmSLMA::smk::gaussian-assigned") test_that("simple glmSLMA, gaussian-assigned", { glmSLMA.res <- ds.glmSLMA('D$LAB_TSC~D$LAB_TRIG', family="gaussian", newobj="glmSLMA_1.newobj") expect_length(glmSLMA.res, 9) expect_equal(glmSLMA.res$num.valid.studies, 3) expect_true("matrix" %in% class(glmSLMA.res$betamatrix.all)) expect_true("matrix" %in% class(glmSLMA.res$sematrix.all)) expect_true("matrix" %in% class(glmSLMA.res$betamatrix.valid)) expect_true("matrix" %in% class(glmSLMA.res$sematrix.valid)) expect_true("matrix" %in% class(glmSLMA.res$SLMA.pooled.ests.matrix)) expect_length(glmSLMA.res$output.summary, 5) expect_true("matrix" %in% class(glmSLMA.res$output.summary$input.beta.matrix.for.SLMA)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$input.se.matrix.for.SLMA)) expect_length(glmSLMA.res$output.summary$study1, 29) expect_true("family" %in% class(glmSLMA.res$output.summary$study1$family)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$study1$coefficients)) expect_equal(glmSLMA.res$output.summary$study1$rank, 2) expect_equal(glmSLMA.res$output.summary$study1$aic, 5460.549, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study1$iter, 2) expect_equal(glmSLMA.res$output.summary$study1$contrasts, NULL) expect_equal(glmSLMA.res$output.summary$study1$dispersion, 1.211496, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study1$Ntotal, 2163) expect_equal(glmSLMA.res$output.summary$study1$Nvalid, 1801) expect_equal(glmSLMA.res$output.summary$study1$Nmissing, 362) expect_length(glmSLMA.res$output.summary$study2, 29) expect_true("family" %in% class(glmSLMA.res$output.summary$study2$family)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$study2$coefficients)) expect_equal(glmSLMA.res$output.summary$study2$rank, 2) expect_equal(glmSLMA.res$output.summary$study2$aic, 7490.000, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study2$iter, 2) expect_equal(glmSLMA.res$output.summary$study2$contrasts, NULL) expect_equal(glmSLMA.res$output.summary$study2$dispersion, 1.13414, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study2$Ntotal, 3088) expect_equal(glmSLMA.res$output.summary$study2$Nvalid, 2526) expect_equal(glmSLMA.res$output.summary$study2$Nmissing, 562) expect_length(glmSLMA.res$output.summary$study3, 29) expect_true("family" %in% class(glmSLMA.res$output.summary$study3$family)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$study3$coefficients)) expect_equal(glmSLMA.res$output.summary$study3$rank, 2) expect_equal(glmSLMA.res$output.summary$study3$aic, 10256.000, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study3$iter, 2) expect_equal(glmSLMA.res$output.summary$study3$contrasts, NULL) expect_equal(glmSLMA.res$output.summary$study3$dispersion, 1.12, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study3$Ntotal, 4128) expect_equal(glmSLMA.res$output.summary$study3$Nvalid, 3473) expect_equal(glmSLMA.res$output.summary$study3$Nmissing, 655) expect_length(glmSLMA.res$is.object.created, 1) expect_equal(glmSLMA.res$is.object.created, "A data object has been created in all specified data sources") expect_length(glmSLMA.res$validity.check, 1) expect_equal(glmSLMA.res$validity.check, " appears valid in all sources") }) context("ds.glmSLMA::smk::binomial") test_that("simple glmSLMA, binomial", { ds.asCharacter('D$MEDI_LPD', 'str.medi.lpd') ds.asNumeric('str.medi.lpd', 'num.medi.lpd') ds.asCharacter('D$GENDER', 'str.gender') ds.asNumeric('str.gender', 'num.gender') ds.asCharacter('D$DIS_DIAB', 'str.dis.diab') ds.asNumeric('str.dis.diab', 'num.dis.diab') glmSLMA.res <- ds.glmSLMA('num.medi.lpd~num.gender*num.dis.diab', family="binomial") expect_length(glmSLMA.res, 9) expect_equal(glmSLMA.res$num.valid.studies, 3) expect_true("matrix" %in% class(glmSLMA.res$betamatrix.all)) expect_true("matrix" %in% class(glmSLMA.res$sematrix.all)) expect_true("matrix" %in% class(glmSLMA.res$betamatrix.valid)) expect_true("matrix" %in% class(glmSLMA.res$sematrix.valid)) expect_true("matrix" %in% class(glmSLMA.res$SLMA.pooled.ests.matrix)) expect_length(glmSLMA.res$output.summary, 5) expect_true("matrix" %in% class(glmSLMA.res$output.summary$input.beta.matrix.for.SLMA)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$input.se.matrix.for.SLMA)) expect_length(glmSLMA.res$output.summary$study1, 29) expect_true("family" %in% class(glmSLMA.res$output.summary$study1$family)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$study1$coefficients)) expect_equal(glmSLMA.res$output.summary$study1$rank, 4) expect_equal(glmSLMA.res$output.summary$study1$aic, 442.507, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study1$iter, 15) expect_equal(glmSLMA.res$output.summary$study1$contrasts, NULL) expect_equal(glmSLMA.res$output.summary$study1$dispersion, 1.000, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study1$Ntotal, 2163) expect_equal(glmSLMA.res$output.summary$study1$Nvalid, 2163) expect_equal(glmSLMA.res$output.summary$study1$Nmissing, 0) expect_length(glmSLMA.res$output.summary$study2, 29) expect_true("family" %in% class(glmSLMA.res$output.summary$study2$family)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$study2$coefficients)) expect_equal(glmSLMA.res$output.summary$study2$rank, 4) expect_equal(glmSLMA.res$output.summary$study2$aic, 568, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study2$iter, 7) expect_equal(glmSLMA.res$output.summary$study2$contrasts, NULL) expect_equal(glmSLMA.res$output.summary$study2$dispersion, 1.00, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study2$Ntotal, 3088) expect_equal(glmSLMA.res$output.summary$study2$Nvalid, 3088) expect_equal(glmSLMA.res$output.summary$study2$Nmissing, 0) expect_length(glmSLMA.res$output.summary$study3, 29) expect_true("family" %in% class(glmSLMA.res$output.summary$study3$family)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$study3$coefficients)) expect_equal(glmSLMA.res$output.summary$study3$rank, 4) expect_equal(glmSLMA.res$output.summary$study3$aic, 673, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study3$iter, 7) expect_equal(glmSLMA.res$output.summary$study3$contrasts, NULL) expect_equal(glmSLMA.res$output.summary$study3$dispersion, 1.00, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study3$Ntotal, 4128) expect_equal(glmSLMA.res$output.summary$study3$Nvalid, 4128) expect_equal(glmSLMA.res$output.summary$study3$Nmissing, 0) expect_length(glmSLMA.res$is.object.created, 1) expect_equal(glmSLMA.res$is.object.created, "A data object has been created in all specified data sources") expect_length(glmSLMA.res$validity.check, 1) expect_equal(glmSLMA.res$validity.check, " appears valid in all sources") }) context("ds.glmSLMA::smk::binomial-assigned") test_that("simple glmSLMA, binomial-assigned", { ds.asCharacter('D$MEDI_LPD', 'str.medi.lpd') ds.asNumeric('str.medi.lpd', 'num.medi.lpd') ds.asCharacter('D$GENDER', 'str.gender') ds.asNumeric('str.gender', 'num.gender') ds.asCharacter('D$DIS_DIAB', 'str.dis.diab') ds.asNumeric('str.dis.diab', 'num.dis.diab') glmSLMA.res <- ds.glmSLMA('num.medi.lpd~num.gender*num.dis.diab', family="binomial", newobj="glmSLMA_2.newobj") expect_length(glmSLMA.res, 9) expect_equal(glmSLMA.res$num.valid.studies, 3) expect_true("matrix" %in% class(glmSLMA.res$betamatrix.all)) expect_true("matrix" %in% class(glmSLMA.res$sematrix.all)) expect_true("matrix" %in% class(glmSLMA.res$betamatrix.valid)) expect_true("matrix" %in% class(glmSLMA.res$sematrix.valid)) expect_true("matrix" %in% class(glmSLMA.res$SLMA.pooled.ests.matrix)) expect_length(glmSLMA.res$output.summary, 5) expect_true("matrix" %in% class(glmSLMA.res$output.summary$input.beta.matrix.for.SLMA)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$input.se.matrix.for.SLMA)) expect_length(glmSLMA.res$output.summary$study1, 29) expect_true("family" %in% class(glmSLMA.res$output.summary$study1$family)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$study1$coefficients)) expect_equal(glmSLMA.res$output.summary$study1$rank, 4) expect_equal(glmSLMA.res$output.summary$study1$aic, 442.507, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study1$iter, 15) expect_equal(glmSLMA.res$output.summary$study1$contrasts, NULL) expect_equal(glmSLMA.res$output.summary$study1$dispersion, 1.000, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study1$Ntotal, 2163) expect_equal(glmSLMA.res$output.summary$study1$Nvalid, 2163) expect_equal(glmSLMA.res$output.summary$study1$Nmissing, 0) expect_length(glmSLMA.res$output.summary$study2, 29) expect_true("family" %in% class(glmSLMA.res$output.summary$study2$family)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$study2$coefficients)) expect_equal(glmSLMA.res$output.summary$study2$rank, 4) expect_equal(glmSLMA.res$output.summary$study2$aic, 568, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study2$iter, 7) expect_equal(glmSLMA.res$output.summary$study2$contrasts, NULL) expect_equal(glmSLMA.res$output.summary$study2$dispersion, 1.00, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study2$Ntotal, 3088) expect_equal(glmSLMA.res$output.summary$study2$Nvalid, 3088) expect_equal(glmSLMA.res$output.summary$study2$Nmissing, 0) expect_length(glmSLMA.res$output.summary$study3, 29) expect_true("family" %in% class(glmSLMA.res$output.summary$study3$family)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$study3$coefficients)) expect_equal(glmSLMA.res$output.summary$study3$rank, 4) expect_equal(glmSLMA.res$output.summary$study3$aic, 673, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study3$iter, 7) expect_equal(glmSLMA.res$output.summary$study3$contrasts, NULL) expect_equal(glmSLMA.res$output.summary$study3$dispersion, 1.00, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study3$Ntotal, 4128) expect_equal(glmSLMA.res$output.summary$study3$Nvalid, 4128) expect_equal(glmSLMA.res$output.summary$study3$Nmissing, 0) expect_length(glmSLMA.res$is.object.created, 1) expect_equal(glmSLMA.res$is.object.created, "A data object has been created in all specified data sources") expect_length(glmSLMA.res$validity.check, 1) expect_equal(glmSLMA.res$validity.check, " appears valid in all sources") }) context("ds.glmSLMA::smk::poisson") test_that("simple glmSLMA, poisson", { glmSLMA.res <- ds.glmSLMA('D$LAB_TSC~D$LAB_TRIG', family="poisson") expect_length(glmSLMA.res, 9) expect_equal(glmSLMA.res$num.valid.studies, 3) expect_true("matrix" %in% class(glmSLMA.res$betamatrix.all)) expect_true("matrix" %in% class(glmSLMA.res$sematrix.all)) expect_true("matrix" %in% class(glmSLMA.res$betamatrix.valid)) expect_true("matrix" %in% class(glmSLMA.res$sematrix.valid)) expect_true("matrix" %in% class(glmSLMA.res$SLMA.pooled.ests.matrix)) expect_length(glmSLMA.res$output.summary, 5) expect_true("matrix" %in% class(glmSLMA.res$output.summary$input.beta.matrix.for.SLMA)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$input.se.matrix.for.SLMA)) expect_length(glmSLMA.res$output.summary$study1, 29) expect_true("family" %in% class(glmSLMA.res$output.summary$study1$family)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$study1$coefficients)) expect_equal(glmSLMA.res$output.summary$study1$rank, 2) expect_equal(glmSLMA.res$output.summary$study1$aic, Inf, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study1$iter, 4) expect_equal(glmSLMA.res$output.summary$study1$contrasts, NULL) expect_equal(glmSLMA.res$output.summary$study1$dispersion, 1.000, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study1$Ntotal, 2163) expect_equal(glmSLMA.res$output.summary$study1$Nvalid, 1801) expect_equal(glmSLMA.res$output.summary$study1$Nmissing, 362) expect_length(glmSLMA.res$output.summary$study2, 29) expect_true("family" %in% class(glmSLMA.res$output.summary$study2$family)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$study2$coefficients)) expect_equal(glmSLMA.res$output.summary$study2$rank, 2) expect_equal(glmSLMA.res$output.summary$study2$aic, Inf, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study2$iter, 4) expect_equal(glmSLMA.res$output.summary$study2$contrasts, NULL) expect_equal(glmSLMA.res$output.summary$study2$dispersion, 1.00, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study2$Ntotal, 3088) expect_equal(glmSLMA.res$output.summary$study2$Nvalid, 2526) expect_equal(glmSLMA.res$output.summary$study2$Nmissing, 562) expect_length(glmSLMA.res$output.summary$study3, 29) expect_true("family" %in% class(glmSLMA.res$output.summary$study3$family)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$study3$coefficients)) expect_equal(glmSLMA.res$output.summary$study3$rank, 2) expect_equal(glmSLMA.res$output.summary$study3$aic, Inf, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study3$iter, 4) expect_equal(glmSLMA.res$output.summary$study3$contrasts, NULL) expect_equal(glmSLMA.res$output.summary$study3$dispersion, 1.00, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study3$Ntotal, 4128) expect_equal(glmSLMA.res$output.summary$study3$Nvalid, 3473) expect_equal(glmSLMA.res$output.summary$study3$Nmissing, 655) expect_length(glmSLMA.res$is.object.created, 1) expect_equal(glmSLMA.res$is.object.created, "A data object has been created in all specified data sources") expect_length(glmSLMA.res$validity.check, 1) expect_equal(glmSLMA.res$validity.check, " appears valid in all sources") }) context("ds.glmSLMA::smk::poisson-assigned") test_that("simple glmSLMA, poisson-assigned", { glmSLMA.res <- ds.glmSLMA('D$LAB_TSC~D$LAB_TRIG', family="poisson", newobj="glmSLMA_3.newobj") expect_length(glmSLMA.res, 9) expect_equal(glmSLMA.res$num.valid.studies, 3) expect_true("matrix" %in% class(glmSLMA.res$betamatrix.all)) expect_true("matrix" %in% class(glmSLMA.res$sematrix.all)) expect_true("matrix" %in% class(glmSLMA.res$betamatrix.valid)) expect_true("matrix" %in% class(glmSLMA.res$sematrix.valid)) expect_true("matrix" %in% class(glmSLMA.res$SLMA.pooled.ests.matrix)) expect_length(glmSLMA.res$output.summary, 5) expect_true("matrix" %in% class(glmSLMA.res$output.summary$input.beta.matrix.for.SLMA)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$input.se.matrix.for.SLMA)) expect_length(glmSLMA.res$output.summary$study1, 29) expect_true("family" %in% class(glmSLMA.res$output.summary$study1$family)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$study1$coefficients)) expect_equal(glmSLMA.res$output.summary$study1$rank, 2) expect_equal(glmSLMA.res$output.summary$study1$aic, Inf, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study1$iter, 4) expect_equal(glmSLMA.res$output.summary$study1$contrasts, NULL) expect_equal(glmSLMA.res$output.summary$study1$dispersion, 1.000, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study1$Ntotal, 2163) expect_equal(glmSLMA.res$output.summary$study1$Nvalid, 1801) expect_equal(glmSLMA.res$output.summary$study1$Nmissing, 362) expect_length(glmSLMA.res$output.summary$study2, 29) expect_true("family" %in% class(glmSLMA.res$output.summary$study2$family)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$study2$coefficients)) expect_equal(glmSLMA.res$output.summary$study2$rank, 2) expect_equal(glmSLMA.res$output.summary$study2$aic, Inf, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study2$iter, 4) expect_equal(glmSLMA.res$output.summary$study2$contrasts, NULL) expect_equal(glmSLMA.res$output.summary$study2$dispersion, 1.00, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study2$Ntotal, 3088) expect_equal(glmSLMA.res$output.summary$study2$Nvalid, 2526) expect_equal(glmSLMA.res$output.summary$study2$Nmissing, 562) expect_length(glmSLMA.res$output.summary$study3, 29) expect_true("family" %in% class(glmSLMA.res$output.summary$study3$family)) expect_true("matrix" %in% class(glmSLMA.res$output.summary$study3$coefficients)) expect_equal(glmSLMA.res$output.summary$study3$rank, 2) expect_equal(glmSLMA.res$output.summary$study3$aic, Inf, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study3$iter, 4) expect_equal(glmSLMA.res$output.summary$study3$contrasts, NULL) expect_equal(glmSLMA.res$output.summary$study3$dispersion, 1.00, tolerance = 0.001) expect_equal(glmSLMA.res$output.summary$study3$Ntotal, 4128) expect_equal(glmSLMA.res$output.summary$study3$Nvalid, 3473) expect_equal(glmSLMA.res$output.summary$study3$Nmissing, 655) expect_length(glmSLMA.res$is.object.created, 1) expect_equal(glmSLMA.res$is.object.created, "A data object has been created in all specified data sources") expect_length(glmSLMA.res$validity.check, 1) expect_equal(glmSLMA.res$validity.check, " appears valid in all sources") }) # # Done # context("ds.glmSLMA::smk::shutdown") test_that("shutdown", { ds_expect_variables(c("D", "new.glm.obj", "glmSLMA_1.newobj", "glmSLMA_2.newobj", "glmSLMA_3.newobj", "num.medi.lpd", "num.dis.diab", "num.gender", "str.medi.lpd", "str.dis.diab", "str.gender")) }) disconnect.studies.dataset.cnsim() context("ds.glmSLMA::smk::done")