library(multinma) library(dplyr) test_that("network must be a network", { m <- "`network` must be an `nma_data` object" expect_error(has_direct(list()), m) expect_error(has_indirect(list()), m) expect_error(get_nodesplits(list()), m) }) thrombo_net <- set_agd_arm(thrombolytics, studyn, trtc, r = r, n = n) thrombo_net2 <- set_agd_arm(thrombolytics, studyn, trtn, r = r, n = n) test_that("treatments must be scalars", { m <- "should be a single integer, string, or factor, naming a treatment" expect_error(has_direct(thrombo_net, 1:2, "SK"), m) expect_error(has_direct(thrombo_net, "SK", 1:2), m) expect_error(has_indirect(thrombo_net, 1:2, "SK"), m) expect_error(has_indirect(thrombo_net, "SK", 1:2), m) }) test_that("treatments must be in network", { m1 <- "`trt1` does not match a treatment in the network" m2 <- "`trt2` does not match a treatment in the network" expect_error(has_direct(thrombo_net, "bad", "SK"), m1) expect_error(has_direct(thrombo_net, "SK", "bad"), m2) expect_error(has_indirect(thrombo_net, "bad", "SK"), m1) expect_error(has_indirect(thrombo_net, "SK", "bad"), m2) expect_error( nma(thrombo_net, consistency = "nodesplit", nodesplit = c("bad", "SK"), prior_intercept = normal(scale = 10), prior_trt = normal(scale = 10)), "The `nodesplit` treatment comparison should match two treatments in the network") }) test_that("trt1 and trt2 must be different", { m <- "`trt1` and `trt2` cannot be the same treatment" expect_error(has_direct(thrombo_net, "SK", "SK"), m) expect_error(has_indirect(thrombo_net, "SK", "SK"), m) expect_error( nma(thrombo_net, consistency = "nodesplit", nodesplit = c("SK", "SK"), prior_intercept = normal(scale = 10), prior_trt = normal(scale = 10)), "`nodesplit` comparison cannot be the same treatment against itself") }) test_that("has_direct and has_indirect outputs are correct", { expect_identical(has_direct(thrombo_net, "TNK", "Acc t-PA"), TRUE) expect_identical(has_direct(thrombo_net, "TNK", "t-PA"), FALSE) expect_identical(has_indirect(thrombo_net, "TNK", "Acc t-PA"), FALSE) expect_identical(has_indirect(thrombo_net, "TNK", "t-PA"), TRUE) expect_identical(has_direct(thrombo_net2, 6, 3), TRUE) expect_identical(has_direct(thrombo_net2, 6, 2), FALSE) expect_identical(has_indirect(thrombo_net2, 6, 3), FALSE) expect_identical(has_indirect(thrombo_net2, 6, 2), TRUE) }) # Output from gemtc::mtc.nodesplit.comparisons() on thrombo network ns_thrombo_gemtc <- tibble::tribble( ~trt1, ~trt2, 1, 2, 1, 3, 1, 5, 1, 7, 1, 8, 1, 9, 2, 7, 2, 8, 2, 9, 3, 4, 3, 5, 3, 7, 3, 8, 3, 9 ) %>% mutate(trt1 = factor(trt1, levels = levels(thrombo_net2$treatments)), trt2 = factor(trt2, levels = levels(thrombo_net2$treatments))) test_that("get_nodesplits() produces correct output for thombolytics network", { expect_identical(get_nodesplits(thrombo_net2), ns_thrombo_gemtc) }) park_net <- set_agd_arm(parkinsons, studyn, trtn, y = y, se = se, trt_ref = 1) # Compare to results in van Valkenhoef paper ns_park_vv <- tibble::tribble( ~trt1, ~trt2, 1, 3, 1, 4, 2, 4, 3, 4 ) %>% mutate(trt1 = factor(trt1, levels = levels(park_net$treatments)), trt2 = factor(trt2, levels = levels(park_net$treatments))) test_that("get_nodesplits() produces correct output for parkinsons network", { expect_identical(get_nodesplits(park_net), ns_park_vv) }) test_that("get_nodesplits() handles repeated treatment arms", { thrombo_net_rep <- set_agd_arm(rbind(thrombolytics, thrombolytics[c(2, 5), ]), studyn, trtn, r = r, n = n) expect_identical(get_nodesplits(thrombo_net_rep), ns_thrombo_gemtc) }) onestudy <- data.frame(study = 1, trt = 1:3, r = 1, n = 1) pair_net <- set_agd_arm(onestudy[1:2, ], study, trt, r = r, n = n) multi_net <- set_agd_arm(onestudy, study, trt, r = r, n = n) test_that("get_nodesplits() returns an empty tibble if no splits to be done", { expect_identical(get_nodesplits(pair_net), tibble(trt1 = factor(levels = levels(pair_net$treatments)), trt2 = factor(levels = levels(pair_net$treatments)))) expect_identical(get_nodesplits(multi_net), tibble(trt1 = factor(levels = levels(multi_net$treatments)), trt2 = factor(levels = levels(multi_net$treatments)))) }) test_that("has_direct and has_indirect work with one study / pairwise MA", { expect_identical(has_direct(pair_net, 1, 2), TRUE) expect_identical(has_direct(multi_net, 1, 2), TRUE) expect_identical(has_indirect(pair_net, 1, 2), FALSE) expect_identical(has_indirect(multi_net, 1, 2), FALSE) }) test_that("nma() nodesplit error if can't split given comparison", { expect_error( nma(thrombo_net, consistency = "nodesplit", nodesplit = c("TNK", "t-PA"), prior_intercept = normal(scale = 10), prior_trt = normal(scale = 10)), "no direct evidence" ) expect_error( nma(thrombo_net, consistency = "nodesplit", nodesplit = c("TNK", "Acc t-PA"), prior_intercept = normal(scale = 10), prior_trt = normal(scale = 10)), "no independent indirect evidence" ) }) test_that("nma() nodesplit error if no comparisons to split", { m <- "No comparisons to node-split" expect_error( nma(pair_net, consistency = "nodesplit", prior_intercept = normal(scale = 10), prior_trt = normal(scale = 10)), m ) expect_error( nma(multi_net, consistency = "nodesplit", prior_intercept = normal(scale = 10), prior_trt = normal(scale = 10)), m ) }) test_that("nma() nodesplit warning about ignoring comparisons", { expect_warning( nma(thrombo_net, consistency = "nodesplit", nodesplit = data.frame(trt1 = "Acc t-PA", trt2 = c("TNK", "ASPAC")), prior_intercept = normal(scale = 10), prior_trt = normal(scale = 10), test_grad = TRUE), "Ignoring node-split comparisons.+Acc t-PA vs\\. TNK" ) }) test_that("nma() nodesplit argument validation", { m1 <- "The data frame passed to `nodesplit` should have two columns" expect_error( nma(thrombo_net, consistency = "nodesplit", nodesplit = data.frame(), prior_intercept = normal(scale = 10), prior_trt = normal(scale = 10)), m1 ) expect_error( nma(thrombo_net, consistency = "nodesplit", nodesplit = data.frame(a = 1, b = 2, c = 3), prior_intercept = normal(scale = 10), prior_trt = normal(scale = 10)), m1 ) m2 <- "`nodesplit` should either be a length 2 vector or a 2 column data frame" expect_error( nma(thrombo_net, consistency = "nodesplit", nodesplit = list(), prior_intercept = normal(scale = 10), prior_trt = normal(scale = 10)), m2 ) expect_error( nma(thrombo_net, consistency = "nodesplit", nodesplit = 1:3, prior_intercept = normal(scale = 10), prior_trt = normal(scale = 10)), m2 ) }) thrombo_ns1 <- nma(thrombo_net, consistency = "nodesplit", nodesplit = c("SK", "t-PA"), prior_intercept = normal(scale = 10), prior_trt = normal(scale = 10), test_grad = TRUE) thrombo_ns2<- nma(thrombo_net, consistency = "nodesplit", nodesplit = data.frame(trt1 = "SK", trt2 = "t-PA"), prior_intercept = normal(scale = 10), prior_trt = normal(scale = 10), test_grad = TRUE) test_that("nma() nodesplit produces correct classes", { expect_s3_class(thrombo_ns1, "nma_nodesplit") expect_s3_class(thrombo_ns2, "nma_nodesplit_df") }) test_that("summary method consistency argument requires consistency model", { m <- "should be a fitted consistency model" expect_error(summary(thrombo_ns1, consistency = thrombo_ns1), m) expect_error(summary(thrombo_ns2, consistency = thrombo_ns1), m) expect_error(summary(thrombo_ns1, consistency = "bad"), m) expect_error(summary(thrombo_ns2, consistency = "bad"), m) }) test_that("summary method checks nodesplit and consistency models are compatible", { skip_on_cran() m <- "does not match the node-splitting model" suppressWarnings({ thrombo_ns1 <- nma(thrombo_net, consistency = "nodesplit", nodesplit = c("SK", "t-PA"), prior_intercept = normal(scale = 10), prior_trt = normal(scale = 10), iter = 1) thrombo_ns2<- nma(thrombo_net, consistency = "nodesplit", nodesplit = data.frame(trt1 = "SK", trt2 = "t-PA"), prior_intercept = normal(scale = 10), prior_trt = normal(scale = 10), iter = 1) thrombo_re <- nma(thrombo_net, trt_effects = "random", prior_intercept = normal(scale = 10), prior_trt = normal(scale = 10), prior_het = half_normal(2), iter = 1) thrombo_reg <- nma(thrombo_net, regression = ~I(rnorm(102)), prior_intercept = normal(scale = 10), prior_trt = normal(scale = 10), prior_reg = normal(scale = 10), iter = 1) }) expect_error(summary(thrombo_ns1, consistency = thrombo_re), m) expect_error(summary(thrombo_ns2, consistency = thrombo_re), m) expect_error(summary(thrombo_ns1, consistency = thrombo_reg), m) expect_error(summary(thrombo_ns2, consistency = thrombo_reg), m) })