Meta-analysis of Continuous Data

Authors

[Editor] Hu Zheng;

[Contributors]

Note

Hiplot website

This page is the tutorial for source code version of the Hiplot Meta-analysis of Continuous Data plugin. You can also use the Hiplot website to achieve no code ploting. For more information please see the following link:

https://hiplot.cn/basic/meta-cont?lang=en

Setup

  • System Requirements: Cross-platform (Linux/MacOS/Windows)

  • Programming language: R

  • Dependent packages: meta; ggplotify

# Install packages
if (!requireNamespace("meta", quietly = TRUE)) {
  install.packages("meta")
}
if (!requireNamespace("ggplotify", quietly = TRUE)) {
  install.packages("ggplotify")
}

# Load packages
library(meta)
library(ggplotify)

Data Preparation

# Load data
data <- read.delim("files/Hiplot/120-meta-cont-data.txt", header = T)

# Convert data structure
m1 <- metacont(n.e, mean.e, sd.e, n.c, mean.c, sd.c, studlab = Study, data = data,
              sm = "SMD")

# View data
head(data)
  Study n.e mean.e sd.e n.c mean.c  sd.c
1     A  13    5.0 4.70  13   6.50  3.80
2     B  30    4.9 1.71  50   6.10  2.30
3     C  35   22.5 3.44  35  24.90 10.65
4     D  20   12.5 1.47  20  12.30  1.66
5     E   8    6.5 0.76   8   7.38  1.41

Visualization

# Meta-analysis of Continuous Data
p <- as.ggplot(function(){
  meta::forest(m1, layout = "meta")
  })

p
FigureΒ 1: Meta-analysis of Continuous Data