tests/testthat/test-synth_pov.R

In alexWhitworth/synthACS: Synthetic Microdata and Spatial MicroSimulation Modeling for ACS Data

library(testthat)
library(synthACS)

context("synth - poverty status")

test_that("get correct results", {
  # then create multiple examples
  ca <- synthACS:::synth_data_nativ(
    synthACS:::synth_data_emp(synthACS:::synth_data_edu(synthACS:::synth_data_mar(
      synthACS:::synth_data_ag(
        unlist(ca_dat$estimates$age_by_sex[26,])),
      unlist(ca_dat$estimates$marital_status[26,])),
      unlist(ca_dat$estimates$edu[26,])),
      unlist(ca_dat$estimates$emp_status[26,])),
    unlist(ca_dat$estimates$nativity[26,]))
  
  ca_ag1 <- synthACS:::synth_data_pov(synthACS:::synth_data_nativ(
    synthACS:::synth_data_emp(synthACS:::synth_data_edu(synthACS:::synth_data_mar(
      synthACS:::synth_data_ag(unlist(ca_dat$estimates$age_by_sex[1,])),
      unlist(ca_dat$estimates$marital_status[1,])),
      unlist(ca_dat$estimates$edu[1,])),
      unlist(ca_dat$estimates$emp_status[1,])),
      unlist(ca_dat$estimates$nativity[1,])),
    pov_ge_vec= unlist(ca_dat$estimates$pov_status1[1,]), total_pop= ca_dat$estimates$age_by_sex[1,1])
  
  ca_ag2 <- synthACS:::synth_data_pov(ca, pov_ge_vec= unlist(ca_dat$estimates$pov_status1[26,]), 
              total_pop= ca_dat$estimates$age_by_sex[26,1])
  
  ca_ag3 <- synthACS:::synth_data_pov(synthACS:::synth_data_nativ(
    synthACS:::synth_data_emp(synthACS:::synth_data_edu(synthACS:::synth_data_mar(
      synthACS:::synth_data_ag(unlist(ca_dat$estimates$age_by_sex[50,])),
      unlist(ca_dat$estimates$marital_status[50,])),
      unlist(ca_dat$estimates$edu[50,])),
      unlist(ca_dat$estimates$emp_status[50,])),
    unlist(ca_dat$estimates$nativity[50,])),
    pov_ge_vec= unlist(ca_dat$estimates$pov_status1[50,]), total_pop= ca_dat$estimates$age_by_sex[50,1])
  
  ##---------------------------------------------------------------------------
  ## 02. Tests
  ##---------------------------------------------------------------------------
  # test classes, names, dimensions
  expect_true(is.data.frame(ca_ag1[[1]]))
  expect_true(is.data.frame(ca_ag2[[1]]))
  expect_true(is.data.frame(ca_ag3[[1]]))
  expect_true(is.list(ca_ag1))
  expect_equal(length(ca_ag2), 2)
  expect_equal(levels(ca_ag1[[1]]$edu_attain), ca_ag2[[2]])
  
  expect_equal(ncol(ca_ag1[[1]]), ncol(ca_ag2[[1]]))
  expect_equal(ncol(ca_ag1[[1]]), ncol(ca_ag3[[1]]))
  expect_equal(names(ca_ag1[[1]]), names(ca_ag3[[1]]))
  expect_equal(names(ca_ag1[[1]]), 
               c("age", "gender", "marital_status", "edu_attain", "emp_status", "nativity", 
                 "pov_status", "p"))
  
  # test total probabability
  expect_equal(sum(ca_ag1[[1]]$p), 1)
  expect_equal(sum(ca_ag2[[1]]$p), 1)
  expect_equal(sum(ca_ag3[[1]]$p), 1)
  
  # test probability based on conditioning
  expect_equal(tapply(ca_ag2[[1]]$p, ca_ag2[[1]]$emp_status, sum),
               tapply(ca[[1]]$p, ca[[1]]$emp_status, sum))
  expect_equal(tapply(ca_ag2[[1]]$p, ca_ag2[[1]]$gender, sum),
               tapply(ca[[1]]$p, ca[[1]]$gender, sum))
  
})