## ---- include = FALSE--------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- library(viscomp) data("MACE") ## ---- message = FALSE, warning=FALSE------------------------------------------ library(netmeta) data_NMA <- pairwise(studlab = Study, treat = list(treat1, treat2, treat3, treat4), n = list(n1, n2, n3, n4), event = list(event1, event2, event3, event4), data = MACE, sm = "OR" ) net <- netmeta(TE = TE, seTE = seTE, studlab = studlab, treat1 = treat1, treat2 = treat2, data = data_NMA, small.values = "good", ref = "UC") ## ---- fig.width = 8.5, fig.height = 6, out.width="100%"----------------------- compdesc(net) ## ---- fig.width = 7.5, fig.height = 6, out.width="100%"----------------------- compGraph(net, mostF = 10, title = "") ## ---- fig.width = 7.5, fig.height = 6, out.width="100%"----------------------- compGraph(net, mostF = 10, title = "", excl = "UC") ## ---- fig.width = 7.2, fig.height = 6----------------------------------------- heatcomp(net) ## ---- fig.width=10, out.width="100%", fig.height = 7.5------------------------ specc(net) ## ---- fig.width = 8, out.width="100%", fig.height = 7.5----------------------- specc(net, combination = c("A", "A + B", "A + B + C")) ## ---- fig.width = 7.2, fig.height = 7.5, out.width="100%"--------------------- specc(net, components_number = TRUE) ## ---- fig.width = 7.2, fig.height = 7.5, out.width="100%"--------------------- specc(net, components_number = TRUE, groups = c(1, 2, "1-2", "2+")) ## ---- fig.width = 7.2, fig.height = 6----------------------------------------- denscomp(net, combination = "A+B") ## ---- fig.width = 7.2, fig.height = 6----------------------------------------- denscomp(net, combination = c("A", "A + B", "A + B + C")) ## ---- fig.width = 7.2, fig.height = 6----------------------------------------- loccos(net, combination = "A", histogram = FALSE) ## ---- fig.width = 7.2, fig.height = 6----------------------------------------- watercomp(net, combination = "A") ## ---- eval = TRUE------------------------------------------------------------- t1 <- c("A", "B", "C", "A+B", "A+C", "B+C", "A") t2 <- c("C", "A", "A+C", "B+C", "A", "B", "B+C") TE1 <- c(2.12, 3.24, 5.65, -0.60, 0.13, 0.66, 3.28) TE2 <- c(4.69, 2.67, 2.73, -3.41, 1.79, 2.93, 2.51) seTE1 <- rep(0.1, 7) seTE2 <- rep(0.2, 7) study <- paste0("study_", 1:7) data1 <- data.frame("TE" = TE1, "seTE" = seTE1, "treat1" = t1, "treat2" = t2, "studlab" = study, stringsAsFactors = FALSE) data2 <- data.frame("TE" = TE2, "seTE" = seTE2, "treat1" = t1, "treat2" = t2, "studlab" = study, stringsAsFactors = FALSE) net1 <- netmeta(TE = TE, seTE = seTE, studlab = studlab, treat1 = treat1, treat2 = treat2, data = data1, ref = "A") net2 <- netmeta::netmeta(TE = TE, seTE = seTE, studlab = studlab, treat1 = treat1, treat2 = treat2, data = data2, ref = "A") ## ---- fig.width = 7.2, fig.height = 6, out.width="100%"----------------------- rankheatplot(list(net1, net2))