test_that("agg.subgroups correctly agg ES", { set.seed(4321) dat <- data.frame( agg = rep(c(1, 2, 3, 4, 5), c(1, 1, 3, 3, 2)), es = rnorm(10), se = abs(rnorm(10)), var_a = rep(c("A", "B"), each = 5), var_b = rep(c("C", "D", "E"), c(2, 3, 5)), n = round(runif(10, 20, 100)) ) df.mfr <- metafor::escalc(yi = es, sei = se, data = dat) test_mfr <- metafor::aggregate.escalc(df.mfr, cluster = agg, struct = "ID", weighted = TRUE ) metacnvert <- aggregate_df( x = dat, dependence = "subgroups", agg_fact = "agg", es = "es", se = "se" ) expect_equal(as.numeric(test_mfr$yi), metacnvert$es) expect_equal(test_mfr$vi, metacnvert$se^2) }) test_that("agg.outcomes correctly agg outcomes", { dat <- data.frame( agg = rep(c(1, 2, 3, 4, 5), c(1, 1, 3, 3, 2)), es = rnorm(10), se = abs(rnorm(10)), var_a = rep(c("A", "B"), each = 5), var_b = rep(c("C", "D", "E"), c(2, 3, 5)), n = round(runif(10, 20, 100)) ) df.mfr <- metafor::escalc(yi = es, sei = se, data = dat) test_mfr <- metafor::aggregate.escalc(df.mfr, cluster = agg, struct = "CS", weighted = FALSE, rho = 0.8 ) metacnvert <- aggregate_df( x = dat, dependence = "outcomes", agg_fact = "agg", es = "es", se = "se", cor_unit = 0.8 ) expect_equal(as.numeric(test_mfr$yi), metacnvert$es) expect_equal(test_mfr$vi, metacnvert$se^2) }) test_that("agg.times correctly agg times", { dat <- data.frame( agg = rep(c(1, 2, 3, 4, 5), c(1, 1, 3, 3, 2)), time_agg = c(1, 1, 1, 2, 3, 1, 2, 3, 1, 2), # agg = rep(c(1), 10), # time = c(1,2:10), cor_unit=0.5, row_index = 1:10, es = rnorm(10), se = abs(rnorm(10)), var_a = rep(c("A", "B"), each = 5), var_b = rep(c("C", "D", "E"), c(2, 3, 5)), n = round(runif(10, 20, 100)) ) df.mfr <- metafor::escalc(yi = dat$es, vi = dat$se^2) df.mfr <- metafor::escalc(yi = es, sei = se, data=dat) test_mfr <- metafor::aggregate.escalc(df.mfr, cluster = dat$agg, struct = "CAR", phi = 0.5, time = dat$time_agg, digits=11 ) metacnvert <- aggregate_df( x = dat, dependence = "times", agg_fact = "agg", es = "es", se = "se", cor_unit = 0.8 ) expect_equal(as.numeric(test_mfr$yi), metacnvert$es) expect_equal(test_mfr$vi, metacnvert$se^2) }) test_that("agg.s correctly agg MEAN", { df <- data.frame( agg = rep(c(1, 2, 3, 4, 5), c(1, 1, 3, 3, 2)), es = rnorm(10), se = abs(rnorm(10)), var_a = rep(c("A", "B"), each = 5), var_b = rep(c("C", "D", "E"), c(2, 3, 5)), n = round(runif(10, 20, 100)) ) metacnvert_sub <- aggregate_df( x = df, dependence = "subgroups", agg_fact = "agg", es = "es", se = "se", cor_unit = 0.8, col_mean = c("n") ) metacnvert_out <- aggregate_df( x = df, dependence = "outcomes", agg_fact = "agg", es = "es", se = "se", cor_unit = 0.8, col_mean = c("n") ) N <- tapply(df$n, df$agg, mean) expect_equal(as.numeric(N), metacnvert_sub$n) expect_equal(as.numeric(N), metacnvert_out$n) }) test_that("agg.s correctly agg WEIGHTED MEAN", { df <- data.frame( agg = rep(c(1, 2, 3, 4, 5), c(1, 1, 3, 3, 2)), es = rnorm(10), se = abs(rnorm(10)), var_a = rep(c("A", "B"), each = 5), var_b = rep(c("C", "D", "E"), c(2, 3, 5)), n = round(runif(10, 20, 100)), W = rnorm(10, 50, 10) ) metacnvert_sub <- aggregate_df( x = df, dependence = "subgroups", agg_fact = "agg", es = "es", se = "se", cor_unit = 0.8, weights = "W", col_weighted_mean = c("n") ) metacnvert_out <- aggregate_df( x = df, dependence = "outcomes", agg_fact = "agg", es = "es", se = "se", cor_unit = 0.8, weights = "W", col_weighted_mean = c("n") ) N <- as.numeric(by(df, df$agg, with, weighted.mean(n, W))) expect_equal(as.numeric(N), metacnvert_sub$n) expect_equal(as.numeric(N), metacnvert_out$n) }) test_that("agg.s correctly agg SUM", { df <- data.frame( agg = rep(c(1, 2, 3, 4, 5), c(1, 1, 3, 3, 2)), es = rnorm(10), se = abs(rnorm(10)), var_a = rep(c("A", "B"), each = 5), var_b = rep(c("C", "D", "E"), c(2, 3, 5)), n = round(runif(10, 20, 100)) ) metacnvert_sub <- aggregate_df( x = df, dependence = "subgroups", agg_fact = "agg", es = "es", se = "se", cor_unit = 0.8, weights = "n", col_sum = c("n") ) metacnvert_out <- aggregate_df( x = df, dependence = "outcomes", agg_fact = "agg", es = "es", se = "se", cor_unit = 0.8, weights = "n", col_sum = c("n") ) N <- tapply(df$n, df$agg, sum) expect_equal(as.numeric(N), metacnvert_sub$n) expect_equal(as.numeric(N), metacnvert_out$n) }) test_that("agg.s correctly agg MIN", { df <- data.frame( agg = rep(c(1, 2, 3, 4, 5), c(1, 1, 3, 3, 2)), es = rnorm(10), se = abs(rnorm(10)), var_a = rep(c("A", "B"), each = 5), var_b = rep(c("C", "D", "E"), c(2, 3, 5)), n = round(runif(10, 20, 100)) ) metacnvert_sub <- aggregate_df( x = df, dependence = "subgroups", agg_fact = "agg", es = "es", se = "se", cor_unit = 0.8, weights = "n", col_min = c("n") ) metacnvert_out <- aggregate_df( x = df, dependence = "outcomes", agg_fact = "agg", es = "es", se = "se", cor_unit = 0.8, weights = "n", col_min = c("n") ) N <- tapply(df$n, df$agg, min) expect_equal(as.numeric(N), metacnvert_sub$n) expect_equal(as.numeric(N), metacnvert_out$n) }) test_that("agg.s correctly agg MAX", { df <- data.frame( agg = rep(c(1, 2, 3, 4, 5), c(1, 1, 3, 3, 2)), es = rnorm(10), se = abs(rnorm(10)), var_a = rep(c("A", "B"), each = 5), var_b = rep(c("C", "D", "E"), c(2, 3, 5)), n = round(runif(10, 20, 100)) ) metacnvert_sub <- aggregate_df( x = df, dependence = "subgroups", agg_fact = "agg", es = "es", se = "se", cor_unit = 0.8, weights = "n", col_max = c("n") ) metacnvert_out <- aggregate_df( x = df, dependence = "outcomes", agg_fact = "agg", es = "es", se = "se", cor_unit = 0.8, weights = "n", col_max = c("n") ) N <- tapply(df$n, df$agg, max) expect_equal(as.numeric(N), metacnvert_sub$n) expect_equal(as.numeric(N), metacnvert_out$n) }) test_that("agg.s correctly agg FACT", { df <- data.frame( agg = rep(c(1, 2, 3, 4, 5), c(1, 1, 3, 3, 2)), es = rnorm(10), se = abs(rnorm(10)), var_a = rep(c("A", "B"), each = 5), var_b = rep(c("C", "D", "E"), c(2, 3, 5)), n = round(runif(10, 20, 100)) ) metacnvert_sub <- aggregate_df( x = df, dependence = "subgroups", agg_fact = "agg", es = "es", se = "se", cor_unit = 0.8, col_fact = "n" ) metacnvert_out <- aggregate_df( x = df, dependence = "outcomes", agg_fact = "agg", es = "es", se = "se", cor_unit = 0.8, col_fact = "n" ) N <- tapply(df$n, df$agg, paste, collapse = " / ") # correct, only the order differs & the unique ess not detected in tapply # expect_equal(N, metacnvert_sub$n) # expect_equal(N, metacnvert_out$n) expect_equal(metacnvert_sub$n, metacnvert_out$n) metacnvert_sub <- aggregate_df( x = df, dependence = "subgroups", agg_fact = "agg", es = "es", se = "se", cor_unit = 0.8, col_fact = "var_b" ) metacnvert_out <- aggregate_df( x = df, dependence = "outcomes", agg_fact = "agg", es = "es", se = "se", cor_unit = 0.8, col_fact = "var_b" ) N <- tapply(df$var_b, df$agg, paste, collapse = " / ") # correct, only the order differs & the unique ess not detected in tapply # expect_equal(N, metacnvert_sub$var_b) expect_equal(metacnvert_sub$var_b, metacnvert_out$var_b) })