R Under development (unstable) (2024-01-12 r85803 ucrt) -- "Unsuffered Consequences"
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> # NOTE: The estimators of the population mean for a model without a
> #       regression intercept are excluded from the test because they
> #       differ from the implementation based on survey::calibrate
> suppressPackageStartupMessages(library("survey"))
> library("robsurvey", quietly = TRUE)
> source("check_functions.R")
> 
> #===============================================================================
> # 1 MU284strat data (weights are calibrated to N)
> #===============================================================================
> dataset <- "MU284strat"
> dn <- svydesign(ids = ~LABEL, strata = ~Stratum, fpc = ~fpc,
+          weights = ~weights, data = MU284strat)
> 
> f0 <- RMT85 ~ -1 + P85 + S82 + CS82
> f <- RMT85 ~ P85 + S82 + CS82
> 
> N <- 284
> aux_totals <- c(P85 = 8339, S82 = 13500, CS82 = 2583)
> 
> #--------------------------------------
> # 1.1 total
> #--------------------------------------
> 
> # GREG total with intercept
> ref <- svytotal(~RMT85, calibrate(dn, f, c("(Intercept)" = N, aux_totals)))
> est <- svytotal_reg(svyreg(f, dn), aux_totals, N, type = "ADU")
> check(ref, est, dataset, "total with intercept")
> # type "projective" and "ADU" coincide
> est <- svytotal_reg(svyreg(f, dn), aux_totals, N, type = "projective")
> check(ref, est, dataset, "total with intercept: projective")
> 
> # GREG total with intercept + heteroscedasticity
> ref <- svytotal(~RMT85, calibrate(dn, f, c("(Intercept)" = N, aux_totals),
+     variance = MU284strat$P85))
> est <- svytotal_reg(svyreg(f, dn, var = ~ P85), aux_totals, N, type = "ADU")
> check(ref, est, dataset, "total with intercept: hetero")
> 
> # GREG total without intercept
> ref <- svytotal(~RMT85, calibrate(dn, f0, aux_totals))
> est <- svytotal_reg(svyreg(f0, dn), aux_totals, type = "ADU")
> check(ref, est, dataset, "total w/o intercept")
> 
> #--------------------------------------
> # 1.2 mean
> #--------------------------------------
> # GREG mean with intercept
> ref <- svymean(~RMT85, calibrate(dn, f, c("(Intercept)" = N, aux_totals)))
> est <- svymean_reg(svyreg(f, dn), aux_totals, N, type = "ADU")
> check(ref, est, dataset, "mean with intercept")
> 
> # GREG mean with intercept + heteroscedasticity
> ref <- svymean(~RMT85, calibrate(dn, f, c("(Intercept)" = N, aux_totals),
+     variance = MU284strat$P85))
> est <- svymean_reg(svyreg(f, dn, var = ~ P85), aux_totals, N, type = "ADU")
> check(ref, est, dataset, "mean with intercept: hetero")
> 
> # GREG mean without intercept, see NOTE:
> if (FALSE) {
+     ref <- svymean(~RMT85, calibrate(dn, f0, aux_totals))
+     est <- svymean_reg(svyreg(f0, dn), aux_totals, N, type = "ADU")
+     check(ref, est, dataset, "mean w/o intercept")
+ }
> #===============================================================================
> # 2 workplace data (weights are calibrated to N)
> #===============================================================================
> dataset <- "workplace"
> dn <- svydesign(ids = ~ID, strata = ~strat, fpc = ~fpc, weights = ~weight,
+     data = workplace)
> 
> f0 <- payroll ~ -1 + employment
> f <- payroll ~ employment
> 
> N <- 86514
> aux_totals <- c(employment = 953555 * 1.05)
> 
> #--------------------------------------
> # 2.1 total
> #--------------------------------------
> # GREG total with intercept
> ref <- svytotal(~payroll, calibrate(dn, f, c("(Intercept)" = N, aux_totals)))
> est <- svytotal_reg(svyreg(f, dn), aux_totals, N, type = "ADU")
> check(ref, est, dataset, "total with intercept")
> # type "projective" and "ADU" coincide
> est <- svytotal_reg(svyreg(f, dn), aux_totals, N, type = "projective")
> check(ref, est, dataset, "total with intercept: projective")
> 
> # GREG total without intercept
> ref <- svytotal(~payroll, calibrate(dn, f0, aux_totals))
> est <- svytotal_reg(svyreg(f0, dn), aux_totals, type = "ADU")
> check(ref, est, dataset, "total w/o intercept")
> 
> # GREG total without intercept + heteroscedasticity (ratio estimator)
> ref <- svytotal(~payroll, calibrate(dn, f0, aux_totals,
+     variance = workplace$employment))
> est <- svytotal_reg(svyreg(f0, dn, var = ~employment), aux_totals,
+     type = "ADU")
> check(ref, est, dataset, "total w/o intercept: hetero")
> 
> #--------------------------------------
> # 2.2 mean
> #--------------------------------------
> # GREG mean with intercept
> ref <- svymean(~payroll, calibrate(dn, f, c("(Intercept)" = N, aux_totals)))
> est <- svymean_reg(svyreg(f, dn), aux_totals, N, type = "ADU")
> check(ref, est, dataset, "mean with intercept")
> 
> # GREG mean without intercept; see NOTE:
> if (FALSE) {
+     ref <- svymean(~payroll, calibrate(dn, f0, aux_totals))
+     est <- svymean_reg(svyreg(f0, dn), aux_totals, N, type = "ADU")
+     check(ref, est, dataset, "mean w/o intercept")
+ }
> 
> # GREG mean without intercept + heteroscedasticity (ratio estimator); see NOTE:
> if (FALSE) {
+     ref <- svymean(~payroll, calibrate(dn, f0, aux_totals,
+         variance = workplace$employment))
+     est <- svymean_reg(svyreg(f0, dn, var = ~employment), aux_totals, N,
+         type = "ADU")
+     check(ref, est, dataset, "mean w/o intercept: hetero")
+ }
> 
> #===============================================================================
> # 3 workplace data (weights are NOT calibrated to N)
> #===============================================================================
> dataset <- "workplace"
> # modify workplace data (mulitply weights of the first unit in each stratum
> # by 0.25; thus, the weights are not calibrated)
> wp <- workplace
> wp[wp$ID == 2, "weight"] <- 0.25 * wp[wp$ID == 2, "weight"]
> wp[wp$ID == 1, "weight"] <- 0.25 * wp[wp$ID == 1, "weight"]
> wp[wp$ID == 7, "weight"] <- 0.25 * wp[wp$ID == 7, "weight"]
> dn <- svydesign(ids = ~ID, strata = ~strat, fpc = ~fpc, weights = ~weight,
+     data = wp)
> 
> #--------------------------------------
> # 3.1 total
> #--------------------------------------
> # GREG total with intercept
> ref <- svytotal(~payroll, calibrate(dn, f, c("(Intercept)" = N, aux_totals)))
> est <- svytotal_reg(svyreg(f, dn), aux_totals, N, type = "ADU")
> check(ref, est, paste0(dataset, " (not calibrated)"), "total with intercept")
> # type "projective" and "ADU" coincide
> est <- svytotal_reg(svyreg(f, dn), aux_totals, N, type = "projective")
> check(ref, est, paste0(dataset, " (not calibrated)"),
+     "total with intercept: projective")
> 
> # GREG total without intercept
> ref <- svytotal(~payroll, calibrate(dn, f0, aux_totals))
> est <- svytotal_reg(svyreg(f0, dn), aux_totals, type = "ADU")
> check(ref, est, paste0(dataset, " (not calibrated)"), "total w/o intercept")
> 
> # GREG total without intercept + heteroscedasticity (ratio estimator)
> ref <- svytotal(~payroll, calibrate(dn, f0, aux_totals,
+     variance = wp$employment))
> est <- svytotal_reg(svyreg(f0, dn, var = ~employment), aux_totals,
+     type = "ADU")
> check(ref, est, paste0(dataset, " (not calibrated)"),
+     "total w/o intercept: hetero")
> 
> #--------------------------------------
> # 3.2 mean
> #--------------------------------------
> # GREG mean with intercept
> ref <- svymean(~payroll, calibrate(dn, f, c("(Intercept)" = N, aux_totals)))
> est <- svymean_reg(svyreg(f, dn), aux_totals, N, type = "ADU")
> check(ref, est, paste0(dataset, " (not calibrated)"), "mean with intercept")
> 
> # GREG mean without intercept; see NOTE:
> if (FALSE) {
+     ref <- svymean(~payroll, calibrate(dn, f0, aux_totals))
+     est <- svymean_reg(svyreg(f0, dn), aux_totals, N, type = "ADU")
+     check(ref, est, paste0(dataset, " (not calibrated)"), "mean w/o intercept")
+ }
> 
> # GREG mean without intercept + heteroscedasticity (ratio estimator); see NOTE:
> if (FALSE) {
+     ref <- svymean(~payroll, calibrate(dn, f0, aux_totals,
+         variance = wp$employment))
+     est <- svymean_reg(svyreg(f0, dn, var = ~employment), aux_totals, N,
+         type = "ADU")
+     check(ref, est, paste0(dataset, " (not calibrated)"),
+         "mean w/o intercept: hetero")
+ }
> 
> proc.time()
   user  system elapsed 
   1.20    0.09    1.28