context("Svyiqalpha output survey.design and svyrep.design")

skip_on_cran()

library(laeken)
library(survey)


data(api)
dstrat1 <- convey_prep(svydesign(id =  ~ 1, data = apistrat))
test_that("svyiqalpha works on unweighted designs", {
  svyiqalpha( ~ api00, design = dstrat1, alpha = .2)
})


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 <- svyiqalpha(~ eqincome , design = des_eusilc , alpha = .20)


a2 <-
  svyby(
    ~ eqincome,
    by = ~ hsize,
    design = des_eusilc,
    FUN = svyiqalpha,
    alpha = .20
  )

b1 <-
  svyiqalpha(~ eqincome , design = des_eusilc_rep , alpha = .20)


b2 <-
  svyby(
    ~ eqincome,
    by = ~ hsize,
    design = des_eusilc_rep,
    FUN = svyiqalpha,
    alpha = .20
  )


cv_dif1 <- abs(cv(a1) - cv(b1))
cv_diff2 <- max(abs(SE(a2) / coef(a2) - SE(b2) / coef(b2)))


test_that("output svyiqalpha", {
  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(cv_dif1, coef(a1) * 0.05) # the difference between CVs should be less than 5% of the coefficient, otherwise manually set it
  expect_lte(cv_diff2, max(coef(a2)) * 0.1) # the difference between CVs should be less than 10% of the maximum coefficient, otherwise manually set it
  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)))
})





# 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 <- svyiqalpha(~ eqincome , design = dbd_eusilc , alpha = .20)
c2 <-
  svyby(
    ~ eqincome,
    by = ~ hsize,
    design = dbd_eusilc,
    FUN = svyiqalpha ,
    alpha = .20
  )

dbRemoveTable(conn , 'eusilc')
dbDisconnect(conn)

test_that("database svyiqalpha", {
  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 <-
  svyiqalpha(~ eqincome ,
             design = subset(des_eusilc , hsize == 1) ,
             alpha = .20)
sby_des <-
  svyby(
    ~ eqincome,
    by = ~ hsize,
    design = des_eusilc,
    FUN = svyiqalpha ,
    alpha = .20
  )
sub_rep <-
  svyiqalpha(~ eqincome ,
             design = subset(des_eusilc_rep , hsize == 1) ,
             alpha = .20)
sby_rep <-
  svyby(
    ~ eqincome,
    by = ~ hsize,
    design = des_eusilc_rep,
    FUN = svyiqalpha ,
    alpha = .20
  )

test_that("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 <-
  svyiqalpha(~ eqincome ,
             design = subset(dbd_eusilc , hsize == 1) ,
             alpha = .20)
sby_dbd <-
  svyby(
    ~ eqincome,
    by = ~ hsize,
    design = dbd_eusilc,
    FUN = svyiqalpha ,
    alpha = .20
  )
sub_dbr <-
  svyiqalpha(~ eqincome ,
             design = subset(dbd_eusilc_rep , hsize == 1) ,
             alpha = .20)
sby_dbr <-
  svyby(
    ~ eqincome,
    by = ~ hsize,
    design = dbd_eusilc_rep,
    FUN = svyiqalpha ,
    alpha = .20
  )

dbRemoveTable(conn , 'eusilc')
dbDisconnect(conn)


# compare database-backed designs to non-database-backed designs
test_that("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
test_that("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])
})