context("Rmpg output survey.design and svyrep.design") skip_on_cran() library(laeken) library(survey) data(api) dstrat1 <- convey_prep(svydesign(id = ~ 1, data = apistrat)) expect_equal(as.numeric(coef(svyrmpg( ~ api00, design = dstrat1))),NA_real_) test_that("svyrmpg works on unweighted designs", { expect_equal(SE(svyrmpg( ~ api00, design = dstrat1, percent = 1))[1],0.0172573) }) data(eusilc) names(eusilc) <- tolower(names(eusilc)) des_eusilc <- svydesign( ids = ~ rb030, strata = ~ db040, weights = ~ rb050, data = eusilc ) des_eusilc <- convey_prep(des_eusilc) des_eusilc_rep <- as.svrepdesign(des_eusilc, type = "bootstrap") des_eusilc_rep <- convey_prep(des_eusilc_rep) a1 <- svyrmpg( ~ eqincome, design = des_eusilc) a2 <- svyby( ~ eqincome, by = ~ hsize, design = subset(des_eusilc , hsize < 8) , FUN = svyrmpg ) b1 <- svyrmpg( ~ eqincome, design = des_eusilc_rep) b2 <- svyby( ~ eqincome, by = ~ hsize, design = subset(des_eusilc_rep, hsize < 8) , FUN = svyrmpg ) rel_error1 <- abs(SE(a1) - SE(b1)) / SE(a1) rel_error2 <- max(abs(SE(a2) - SE(b2)) / SE(a2)) test_that("output svyrmpg", { expect_is(coef(a1), "numeric") expect_is(coef(a2), "numeric") expect_is(coef(b1), "numeric") expect_is(coef(b2), "numeric") expect_equal(coef(a1), coef(b1)) expect_equal(coef(a2), coef(b2)) #expect_lte(rel_error1,.1) #expect_lte(rel_error1,.2) expect_is(SE(a1), "matrix") expect_is(SE(a2), "numeric") expect_is(SE(b1), "numeric") expect_is(SE(b2), "numeric") expect_lte(confint(a1)[1], coef(a1)) expect_gte(confint(a1)[2], coef(a1)) expect_lte(confint(b1)[, 1], coef(b1)) expect_gte(confint(b1)[2], coef(b1)) expect_equal(sum(confint(a2)[, 1] <= coef(a2)), length(coef(a2))) expect_equal(sum(confint(a2)[, 2] >= coef(a2)), length(coef(a2))) expect_equal(sum(confint(b2)[, 1] <= coef(b2)), length(coef(b2))) expect_equal(sum(confint(b2)[, 2] >= coef(b2)), length(coef(b2))) }) test_that("database svyrmpg", { skip_on_cran() # database-backed design library(RSQLite) library(DBI) dbfile <- tempfile() conn <- dbConnect(RSQLite::SQLite() , dbfile) dbWriteTable(conn , 'eusilc' , eusilc) dbd_eusilc <- svydesign( ids = ~ rb030 , strata = ~ db040 , weights = ~ rb050 , data = "eusilc", dbname = dbfile, dbtype = "SQLite" ) dbd_eusilc <- convey_prep(dbd_eusilc) c1 <- svyrmpg(~ eqincome , design = dbd_eusilc) c2 <- svyby( ~ eqincome, by = ~ hsize, design = subset(dbd_eusilc , hsize < 8) , FUN = svyrmpg ) dbRemoveTable(conn , 'eusilc') dbDisconnect(conn) expect_equal(coef(a1), coef(c1)) expect_equal(coef(a2), coef(c2)) expect_equal(SE(a1), SE(c1)) expect_equal(SE(a2), SE(c2)) # compare subsetted objects to svyby objects sub_des <- svyrmpg(~ eqincome , design = subset(des_eusilc , hsize == 1)) sby_des <- svyby( ~ eqincome, by = ~ hsize, design = subset(des_eusilc , hsize < 8) , FUN = svyrmpg ) sub_rep <- svyrmpg(~ eqincome , design = subset(des_eusilc_rep , hsize == 1)) sby_rep <- svyby( ~ eqincome, by = ~ hsize, design = subset(des_eusilc_rep , hsize < 8) , FUN = svyrmpg ) # subsets equal svyby expect_equal(as.numeric(coef(sub_des)), as.numeric(coef(sby_des))[1]) expect_equal(as.numeric(coef(sub_rep)), as.numeric(coef(sby_rep))[1]) expect_equal(as.numeric(SE(sub_des)), as.numeric(SE(sby_des))[1]) expect_equal(as.numeric(SE(sub_rep)), as.numeric(SE(sby_rep))[1]) # coefficients should match across svydesign & svrepdesign expect_equal(as.numeric(coef(sub_des)), as.numeric(coef(sby_rep))[1]) # coefficients of variation should be within five percent cv_dif <- abs(cv(sub_des) - cv(sby_rep)[1]) expect_lte(cv_dif, 5) # second run of database-backed designs # # database-backed design library(RSQLite) library(DBI) dbfile <- tempfile() conn <- dbConnect(RSQLite::SQLite() , dbfile) dbWriteTable(conn , 'eusilc' , eusilc) dbd_eusilc <- svydesign( ids = ~ rb030 , strata = ~ db040 , weights = ~ rb050 , data = "eusilc", dbname = dbfile, dbtype = "SQLite" ) dbd_eusilc <- convey_prep(dbd_eusilc) # create a hacky database-backed svrepdesign object # mirroring des_eusilc_rep dbd_eusilc_rep <- svrepdesign( weights = ~ rb050, repweights = des_eusilc_rep$repweights , scale = des_eusilc_rep$scale , rscales = des_eusilc_rep$rscales , type = "bootstrap" , data = "eusilc" , dbtype = "SQLite" , dbname = dbfile , combined.weights = FALSE ) dbd_eusilc_rep <- convey_prep(dbd_eusilc_rep) sub_dbd <- svyrmpg(~ eqincome , design = subset(dbd_eusilc , hsize == 1)) sby_dbd <- svyby( ~ eqincome, by = ~ hsize, design = subset(dbd_eusilc , hsize < 8) , FUN = svyrmpg ) sub_dbr <- svyrmpg(~ eqincome , design = subset(dbd_eusilc_rep , hsize == 1)) sby_dbr <- svyby( ~ eqincome, by = ~ hsize, design = subset(dbd_eusilc_rep , hsize < 8) , FUN = svyrmpg ) dbRemoveTable(conn , 'eusilc') dbDisconnect(conn) # compare database-backed designs to non-database-backed designs # dbi subsets equal non-dbi subsets expect_equal(coef(sub_des), coef(sub_dbd)) expect_equal(coef(sub_rep), coef(sub_dbr)) expect_equal(SE(sub_des), SE(sub_dbd)) expect_equal(SE(sub_rep), SE(sub_dbr)) # compare database-backed subsetted objects to database-backed svyby objects # dbi subsets equal dbi svyby expect_equal(as.numeric(coef(sub_dbd)), as.numeric(coef(sby_dbd))[1]) expect_equal(as.numeric(coef(sub_dbr)), as.numeric(coef(sby_dbr))[1]) expect_equal(as.numeric(SE(sub_dbd)), as.numeric(SE(sby_dbd))[1]) expect_equal(as.numeric(SE(sub_dbr)), as.numeric(SE(sby_dbr))[1]) })