tol_large = 1e-10

test_that("OR : 2x2", {
  skip_on_cran()
  df <- subset(df.OR.multi, factor == "n-3 fatty acids")

  mcv = metaConvert::es_from_2x2(n_cases_exp = df$n_cases_exp,
                                     n_controls_exp = df$n_controls_exp,
                                 n_cases_nexp = df$n_cases_nexp,
                                 n_controls_nexp = df$n_controls_nexp)
  df.agg.mfr <- metafor::escalc(yi = mcv$logor, sei = mcv$logor_se, data = df)

  df.agg.subgroups <- metafor::aggregate.escalc(
    df.agg.mfr[df.agg.mfr$multiple_es=="groups" &
                 !is.na(df.agg.mfr$multiple_es), ],
    cluster = author,
    struct = "ID",
    weighted = TRUE)

  df.agg.outcomes <- metafor::aggregate.escalc(
    df.agg.mfr[df.agg.mfr$multiple_es=="outcomes" & !is.na(df.agg.mfr$multiple_es), ],
    cluster = author,
    struct = "CS",
    weighted = FALSE,
    rho = 0.5)
  df.mfr <- rbind(df.agg.mfr[is.na(df.agg.mfr$multiple_es), ],
                  df.agg.subgroups,
                  df.agg.outcomes)

  df.umb = subset(df, select=-c(value,ci_lo,ci_up))
  umb = umbrella(df.umb, r = 0.5, mult.level=TRUE)
  df.agg.umb = umb[[1]]$x

  df.mfr <- df.mfr[order(df.mfr$author, df.mfr$year), ]
  df.agg.umb <- df.agg.umb[order(df.agg.umb$author, df.agg.umb$year), ]

  expect_equal(df.agg.umb$value, as.numeric(as.character(df.mfr$yi)),
               tolerance = 1e-10)
  expect_equal(df.agg.umb$se, sqrt(df.mfr$vi), tolerance = 1e-10)
})

# Multiple groups / outcomes: effect size estimates
test_that("OR : value SE", {
  skip_on_cran()
  df <- subset(df.OR.multi, factor == "n-3 fatty acids",
               select = -c(n_cases_exp, n_controls_exp))
  df$se = with(df, (log(ci_up) - log(ci_lo)) / (2*qnorm(.975)))
  df.agg.mfr <- metafor::escalc(yi = log(value), sei = se, data = df)

  df.agg.subgroups <- metafor::aggregate.escalc(
    df.agg.mfr[df.agg.mfr$multiple_es=="groups" &
                 !is.na(df.agg.mfr$multiple_es), ],
    cluster = author,
    struct = "ID",
    weighted = TRUE)

  df.agg.outcomes <- metafor::aggregate.escalc(
    df.agg.mfr[df.agg.mfr$multiple_es=="outcomes" & !is.na(df.agg.mfr$multiple_es), ],
    cluster = author,
    struct = "CS",
    weighted = FALSE,
    rho = 0.5)
  df.mfr <- rbind(df.agg.mfr[is.na(df.agg.mfr$multiple_es), ],
                  df.agg.subgroups,
                  df.agg.outcomes)


  umb = umbrella(df, r = 0.5, mult.level=TRUE)
  df.agg.umb = umb[[1]]$x

  df.mfr <- df.mfr[order(df.mfr$author, df.mfr$year), ]
  df.agg.umb <- df.agg.umb[order(df.agg.umb$author, df.agg.umb$year), ]

  expect_equal(df.agg.umb$value, as.numeric(as.character(df.mfr$yi)),
               tolerance = 1e-10)
  expect_equal(df.agg.umb$se, sqrt(df.mfr$vi), tolerance = 1e-10)
})

test_that("RR : 2x2", {
  skip_on_cran()
  df <- subset(df.OR.multi, factor == "n-3 fatty acids")
  df$measure = "RR"
  mcv = metaConvert::es_from_2x2(n_cases_exp = df$n_cases_exp,
                                 n_controls_exp = df$n_controls_exp,
                                 n_cases_nexp = df$n_cases_nexp,
                                 n_controls_nexp = df$n_controls_nexp)
  df.agg.mfr <- metafor::escalc(yi = mcv$logrr, sei = mcv$logrr_se, data = df)

  df.agg.subgroups <- metafor::aggregate.escalc(
    df.agg.mfr[df.agg.mfr$multiple_es=="groups" &
                 !is.na(df.agg.mfr$multiple_es), ],
    cluster = author,
    struct = "ID",
    weighted = TRUE)

  df.agg.outcomes <- metafor::aggregate.escalc(
    df.agg.mfr[df.agg.mfr$multiple_es=="outcomes" & !is.na(df.agg.mfr$multiple_es), ],
    cluster = author,
    struct = "CS",
    weighted = FALSE,
    rho = 0.5)
  df.mfr <- rbind(df.agg.mfr[is.na(df.agg.mfr$multiple_es), ],
                  df.agg.subgroups,
                  df.agg.outcomes)

  df.umb = subset(df, select=-c(value,ci_lo,ci_up))
  umb = umbrella(df.umb, r = 0.5, mult.level=TRUE)
  df.agg.umb = umb[[1]]$x

  df.mfr <- df.mfr[order(df.mfr$author, df.mfr$year), ]
  df.agg.umb <- df.agg.umb[order(df.agg.umb$author, df.agg.umb$year), ]

  expect_equal(df.agg.umb$value, as.numeric(as.character(df.mfr$yi)),
               tolerance = 1e-10)
  expect_equal(df.agg.umb$se, sqrt(df.mfr$vi), tolerance = 1e-10)
})
test_that("RR : value SE", {
  skip_on_cran()
  df <- subset(df.OR.multi, factor == "n-3 fatty acids")
  df$measure = "RR"
  dfRR = df
  mcv = metaConvert::es_from_2x2(n_cases_exp = df$n_cases_exp,
                                 n_controls_exp = df$n_controls_exp,
                                 n_cases_nexp = df$n_cases_nexp,
                                 n_controls_nexp = df$n_controls_nexp)
  df$value = exp(mcv$logrr)
  df$se = mcv$logrr_se
  df.agg.mfr <- metafor::escalc(yi = mcv$logrr, sei = mcv$logrr_se, data = df)

  df.agg.subgroups <- metafor::aggregate.escalc(
    df.agg.mfr[df.agg.mfr$multiple_es=="groups" &
                 !is.na(df.agg.mfr$multiple_es), ],
    cluster = author,
    struct = "ID",
    weighted = TRUE)

  df.agg.outcomes <- metafor::aggregate.escalc(
    df.agg.mfr[df.agg.mfr$multiple_es=="outcomes" & !is.na(df.agg.mfr$multiple_es), ],
    cluster = author,
    struct = "CS",
    weighted = FALSE,
    rho = 0.5)
  df.mfr <- rbind(df.agg.mfr[is.na(df.agg.mfr$multiple_es), ],
                  df.agg.subgroups,
                  df.agg.outcomes)

  df.umb= subset(df, select=-c(ci_lo,ci_up,n_cases_exp, n_controls_exp))
  umb = umbrella(df.umb, r = 0.5, mult.level=TRUE)
  df.agg.umb = umb[[1]]$x

  df.mfr <- df.mfr[order(df.mfr$author, df.mfr$year), ]
  df.agg.umb <- df.agg.umb[order(df.agg.umb$author, df.agg.umb$year), ]

  expect_equal(df.agg.umb$value, as.numeric(as.character(df.mfr$yi)),
               tolerance = 1e-10)
  expect_equal(df.agg.umb$se, sqrt(df.mfr$vi), tolerance = 1e-10)
})

test_that("HR : value SE", {
  skip_on_cran()
  df <- subset(df.OR.multi, factor == "n-3 fatty acids")
  df$measure = "HR"
  dfRR = df
  mcv = metaConvert::es_from_2x2(n_cases_exp = df$n_cases_exp,
                                 n_controls_exp = df$n_controls_exp,
                                 n_cases_nexp = df$n_cases_nexp,
                                 n_controls_nexp = df$n_controls_nexp)
  df$value = exp(mcv$logrr)
  df$se = mcv$logrr_se
  df.agg.mfr <- metafor::escalc(yi = mcv$logrr, sei = mcv$logrr_se, data = df)

  df.agg.subgroups <- metafor::aggregate.escalc(
    df.agg.mfr[df.agg.mfr$multiple_es=="groups" &
                 !is.na(df.agg.mfr$multiple_es), ],
    cluster = author,
    struct = "ID",
    weighted = TRUE)

  df.agg.outcomes <- metafor::aggregate.escalc(
    df.agg.mfr[df.agg.mfr$multiple_es=="outcomes" & !is.na(df.agg.mfr$multiple_es), ],
    cluster = author,
    struct = "CS",
    weighted = FALSE,
    rho = 0.5)
  df.mfr <- rbind(df.agg.mfr[is.na(df.agg.mfr$multiple_es), ],
                  df.agg.subgroups,
                  df.agg.outcomes)

  df.umb= subset(df, select=-c(ci_lo,ci_up,n_cases_exp, n_controls_exp))
  umb = umbrella(df.umb, r = 0.5, mult.level=TRUE)
  df.agg.umb = umb[[1]]$x

  df.mfr <- df.mfr[order(df.mfr$author, df.mfr$year), ]
  df.agg.umb <- df.agg.umb[order(df.agg.umb$author, df.agg.umb$year), ]

  expect_equal(df.agg.umb$value, as.numeric(as.character(df.mfr$yi)),
               tolerance = 1e-10)
  expect_equal(df.agg.umb$se, sqrt(df.mfr$vi), tolerance = 1e-10)
})

test_that("SMD : value SE", {
  skip_on_cran()
  dfSMD <- subset(df.SMD, factor == "Pharmacological",
                  select=-c(mean_cases, mean_controls))
  dfSMD$author[2] = dfSMD$author[3] <- dfSMD$author[1]
  dfSMD$year[2] = dfSMD$year[3] <- dfSMD$year[1]
  dfSMD$multiple_es = NA
  dfSMD$multiple_es[1:3] <- "outcomes"
  dfSMD$measure = "G"

  dfSMD$author[5] = dfSMD$author[6] <- dfSMD$author[7]
  dfSMD$year[5] = dfSMD$year[6] <- dfSMD$year[7]
  dfSMD$multiple_es[5:7] <- "groups"

  df.agg.mfr <- metafor::escalc(yi = dfSMD$value, sei = dfSMD$se, data = dfSMD)

  df.agg.subgroups <- metafor::aggregate.escalc(
    df.agg.mfr[df.agg.mfr$multiple_es=="groups" &
                 !is.na(df.agg.mfr$multiple_es), ],
    cluster = author,
    struct = "ID",
    weighted = TRUE)

  df.agg.outcomes <- metafor::aggregate.escalc(
    df.agg.mfr[df.agg.mfr$multiple_es=="outcomes" & !is.na(df.agg.mfr$multiple_es), ],
    cluster = author,
    struct = "CS",
    weighted = FALSE,
    rho = 0.5)
  df.mfr <- rbind(df.agg.mfr[is.na(df.agg.mfr$multiple_es), ],
                  df.agg.subgroups,
                  df.agg.outcomes)

  df.umb= subset(dfSMD, select=-c(ci_lo,ci_up))
  umb = umbrella(df.umb, r = 0.5, mult.level=TRUE)
  df.agg.umb = umb[[1]]$x

  df.mfr <- df.mfr[order(df.mfr$author, df.mfr$year), ]
  df.agg.umb <- df.agg.umb[order(df.agg.umb$author, df.agg.umb$year), ]

  expect_equal(df.agg.umb$value, as.numeric(as.character(df.mfr$yi)),
               tolerance = 1e-10)
  expect_equal(df.agg.umb$se, sqrt(df.mfr$vi), tolerance = 1e-10)
})

test_that("MD : value SE", {
  skip_on_cran()
  dfMD <- subset(df.SMD, factor == "Pharmacological",
                  select=-c(mean_cases, mean_controls))
  dfMD$author[2] = dfMD$author[3] <- dfMD$author[1]
  dfMD$year[2] = dfMD$year[3] <- dfMD$year[1]
  dfMD$multiple_es = NA
  dfMD$multiple_es[1:3] <- "outcomes"
  dfMD$measure = "MD"

  dfMD$author[5] = dfMD$author[6] <- dfMD$author[7]
  dfMD$year[5] = dfMD$year[6] <- dfMD$year[7]
  dfMD$multiple_es[5:7] <- "groups"

  df.agg.mfr <- metafor::escalc(yi = dfMD$value, sei = dfMD$se, data = dfMD)

  df.agg.subgroups <- metafor::aggregate.escalc(
    df.agg.mfr[df.agg.mfr$multiple_es=="groups" &
                 !is.na(df.agg.mfr$multiple_es), ],
    cluster = author,
    struct = "ID",
    weighted = TRUE)

  df.agg.outcomes <- metafor::aggregate.escalc(
    df.agg.mfr[df.agg.mfr$multiple_es=="outcomes" & !is.na(df.agg.mfr$multiple_es), ],
    cluster = author,
    struct = "CS",
    weighted = FALSE,
    rho = 0.5)
  df.mfr <- rbind(df.agg.mfr[is.na(df.agg.mfr$multiple_es), ],
                  df.agg.subgroups,
                  df.agg.outcomes)

  df.umb = subset(dfMD, select=-c(ci_lo,ci_up))
  umb = umbrella(df.umb, r = 0.5, mult.level=TRUE)
  df.agg.umb = umb[[1]]$x_md

  df.mfr <- df.mfr[order(df.mfr$author, df.mfr$year), ]
  df.agg.umb <- df.agg.umb[order(df.agg.umb$author, df.agg.umb$year), ]

  expect_equal(df.agg.umb$value, as.numeric(as.character(df.mfr$yi)),
               tolerance = 1e-10)
  expect_equal(df.agg.umb$se, sqrt(df.mfr$vi), tolerance = 1e-10)
})