How could I conduct meta-analysis on percentage outcomes using R?

Question

My example data is as follows:

df <- data.frame(study = c("Hodaie","Kerrigan","Lee","Andrade","Lim"), SR = c(0.5460, 0.2270, 0.7540, 0.6420, 0.5000), SE = c(12.30, 15.70, 12.80, 13.80, 9.00), Patients = c(5, 5, 3, 6, 4))

I want to conduct the meta-analysis with SR(single group percentage), SE (standard error that I can compute based on sample size and percentage), and patients(sample size for each study), and I hope I could get the following forest plot (I found this example in an article, and they also have one group percentage data, but I can't find which R statement or argument they used):

Could anyone tell me which R statement or argument that I could use to conduct the meta-analysis and generate the forest plot above? Thank you!

Answer 1

I am sure there are plenty of ways to do this using packages but it can be accomplished in base R (and there are likely more elegant solutions using base R). The way I do it is to first build a blank plot much larger than the needed graphing portion, then overlay the relevant elements on it. I find one has more control over it this way. A basic example that could get you started is below. If you are new to R (based on your name NewRUser), I suggest running it line-by-line to see how it all works. Again, this is only one way and there are likely better approaches. Good luck!

Sample Data

#### Sample Data (modified from OP)
df <- data.frame(Study = c("Hodaie","Kerrigan","Lee","Andrade","Lim"), 
                 SR = c(0.5460, 0.2270, 0.7540, 0.6420, 0.5000), 
                 SE = c(12.30, 15.70, 12.80, 13.80, 9.00), 
                 Patients = c(5, 5, 3, 6, 4),
                 ci_lo = c(30, -8.0, 50, 37, 32),
                 ci_hi = c(78, 53, 100, 91, 67))

### Set up plotting elements
n.studies <- nrow(df)
yy <- n.studies:1
seqx <- seq(-100, 100, 50)

## blank plot much larger than needed
plot(range(-550, 200), range(0, n.studies), type = 'n', axes = F, xlab = '', ylab = '') #blank plot, much bigger than plotting portion needed
  
# Set up axes
  axis(side = 1, at = seqx, labels = seqx, cex.axis = 1, mgp = c(2, 1.5, 1)) # add axis and label (bottom)
  mtext(side = 1, at = 0, 'Seizure Reduction', line = 2.5, cex = 0.85, padj = 1) 
  axis(side = 3, at = seqx, labels = seqx, cex.axis = 1, mgp = c(2, 1.5, 1)) # add axis and label (top)
  mtext(side = 3, at = 0, 'Seizure Reduction', line = 2.5, cex = 0.85, padj = -1) 

## add lines and dots
 segments(df[, "ci_lo"], yy, df[,"ci_hi"], yy) # add lines
   points(df[,"SR"]*100, yy, pch = 19) # add points
   segments(x0 = 0, y0 = max(yy), y1 = 0, lty = 3, lwd = 0.75) #vertical line @ 0

### Add text information
  
 par(xpd = TRUE) 
  text(x = -550, y = yy, df[,"Study"], pos = 4)
  text(x = -450, y = yy, df[,"SR"]*100, pos = 4)
  text(x = -350, y = yy, df[,"SE"], pos = 4)
  text(x = -250, y = yy, df[,"Patients"], pos = 4)
  text(x = 150, y = yy, paste0(df[,"ci_lo"], "-", df[,"ci_hi"]), pos = 4)
  text(x = c(seq(-550, -250, 100), 150), y = max(yy)+0.75, 
       c(colnames(df)[1:4], "CI"), pos = 4, font = 2)

# Add legend
  legend(x = 50, y = 0.5, c("Point estimate", "95% Confidence interval"), 
         pch = c(19, NA), lty = c(NA, 19), bty = "n", cex = 0.65)