Nothing
test_that("The summary log ORs and between-trial sd agree (no missing outcome data)", {
set.seed(123)
## Example taken from the 'mtc.network' function of the 'gemtc' R-package
data <- read.table(textConnection('
study treatment responders sampleSize
01 A 2 100
01 B 5 100
02 B 6 110
02 C 1 110
03 A 3 60
03 C 4 80
03 B 7 80'), header = TRUE)
network <- gemtc::mtc.network(data)
## Fixed-effect NMA
#node.fe <- gemtc::mtc.nodesplit(network, linearModel = "fixed")
#gemtc.fe <- rbind(summary(node.fe)$dir.effect[3:5], summary(node.fe)$ind.effect[3:5])
#colnames(gemtc.fe) <- rownames(gemtc.fe) <- NULL
## Random-effects NMA
node.re <- gemtc::mtc.nodesplit(network, linearModel = "random", hy.prior = gemtc::mtc.hy.prior("std.dev", "dhnorm", 0, 1))
gemtc.re <- rbind(summary(node.re)$dir.effect[3:5], summary(node.re)$ind.effect[3:5])
colnames(gemtc.re) <- rownames(gemtc.re) <- NULL
## Adjust the example above to run the 'run_model' function of the 'rnmamod' R-package
data.rnmamod <- read.table(textConnection('
t1 t2 t3 r1 r2 r3 n1 n2 n3
1 2 NA 2 5 NA 100 100 NA
2 3 NA 6 1 NA 110 110 NA
1 2 3 3 7 4 60 80 80'), header=TRUE)
## Fixed-effect NMA
#res.fe <- run_model(data = data.rnmamod, measure = "OR", model = "FE", D = 0)
#node.fe2 <- run_nodesplit(res.fe)
#resnode.fe <- rbind(node.fe2$direct[c(3, 5:6)], node.fe2$indirect[c(3, 5:6)])
#colnames(resnode.fe) <- rownames(resnode.fe) <- NULL
## Random-effects NMA
res.re <- run_model(data = data.rnmamod, measure = "OR", model = "RE", heter_prior = list("halfnormal", 0, 1), D = 0, ref = 1)
node.re2 <- run_nodesplit(res.re)
resnode.re <- rbind(node.re2$direct[c(3, 5:6)], node.re2$indirect[c(3, 5:6)])
colnames(resnode.re) <- rownames(resnode.re) <- NULL
#expect_equal(resnode.fe, gemtc.fe, tolerance = 4e-2)
#expect_equal(resnode.re, gemtc.re, tolerance = 4e-2)
})
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