RoB_plot: Risk of bias bar plot

In meta2020/net.meta: The Functions for Network Meta Analysis

Description

To plot risk of bias result.

Usage

RoB_plot(study.CM, rob.ind, lab.size, font.family = "Helvetica")

Arguments

study.CM	contribution matrix
rob.ind	risk of bias or indirectness
lab.size	label size
font.family	"Helvetica" or "Times New Roman"

Value

ggplot object

Examples

LDT1 <- read.csv(system.file("extdata", "HR_SH_D.csv", package = "net.meta"))
trt1 <- read.table(system.file("extdata", "HR_SH_D.txt", package = "net.meta"),
    header=TRUE,quote = '"', stringsAsFactors=FALSE)

trt1$description <- factor(trt1$description, trt1$description)
LDT1$study <- factor(LDT1$study, unique(LDT1$study))

nmt1 <- model_netmeta(long.data = LDT1,
treatment=LDT1$treatment,
id.treatments = trt1,
reference = "A",
outcome = "HR")

name1 <- NULL
for(i in 1:(length(trt1$id)-1)){
  name1 <- c(name1, paste0(trt1$id[i], ":", trt1$id[-(1:i)]))
}

study.CM1 <- studyCM_matrix(name1, nmt1)

study.assess1 <- read.csv(system.file("extdata", "HR_SH_A.csv", package = "net.meta"))

p<-RoB_plot(study.CM1, study.assess1$ROB, lab.size=10)

p<-RoB_plot(study.CM1, study.assess1$IND, lab.size=10)

meta2020/net.meta documentation built on March 30, 2021, 7:31 p.m.