[R-meta] Facing some issues on Meta - regression

[Dr. Guido Schwarzer]

Hi all,

The argument 'backtransf = TRUE' was not recognized by bubble.metareg() for the logit-transformation (and other transformations) as this results in a non-linear regression line. The argument worked for relative effect measures like the odds or risk ratio as a logarithmic scale was be used on the y-axis (in this case the regression line is a straight line).

The development version of meta on GitHub allows now to show the back-transformed proportions on the y-axis (with exception of the Freeman-Tukey transformation which needs an average sample size in the back-transformation). For example, metaprop() with logit-transformed proportions:

remotes::install_github("guido-s/meta")
library("meta")
data(Olkin1995)
m <- metaprop(ev.exp, n.exp, data = Olkin1995)
bubble(metareg(m, year)) 
bubble(metareg(m, year), backtransf = FALSE)

Best,
Guido