[R-meta] question on scatter plot of estimates (Fisher's Z) against the standard error

[Gabriel Cotlier]

Hello all,

I would like to show in a scatter plot the relationship existing between
the estimates (Fisher's z correlation) and a given measure of
uncertainty (e.g., standard error) as is in the funnel plot. My intention
is to obtain the funnel plot as in the function metafor::funnel ()
suppressing all the funnel distribution background and keeping only the
scatter plot. With the aim of having a graph of the relationship between
the data and an uncertainty measure in the data, and if it is also possible, a
numerical measure of uncertainty in addition to the scatter plot graph. Is
this possible?

However, when I tried to calculate the standard error by myself, I did not
get the same result as in the output of the metafor::funnel() function
without the funnel distribution background I wanted to suppress.

## CODE
## the model output is saved in the variable named "funnel_all"
## Estimates Fisher's Z extracted from general model
yi_data <-funnel_all$yi[1:150]

## calculate standard error SE (formula =
sd(estimtes_fisher_z)/sqrt(N_estimtes))

## 1. Directly with the data:
N = 150 # number of samples
SE <- 1/(sd(yi_data)/sqrt(N))

## 2. using a function:
std <- function(x) sd(x)/sqrt(length(x))
SE <- std(yi_data)

Then, in the obtained plot of the estimates (Fisher's z ) against the SE,
the results do not match the same output of the function mertafor::funnel()
but without the funnel distribution in the background of the plot.

How could this be possible to achieve?
Thanks a lot for your guidance and help.
Kind regards,
Gabriel

	[[alternative HTML version deleted]]