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

Gabriel Cotlier g@b|k|m01 @end|ng |rom gm@||@com
Wed Jul 19 07:07:54 CEST 2023


Dear all,

I have already posted this question with no response.
Maybe this time I am luckier and someone with more knowledge than me in the
Metafor package can answer me.

In a nutshell, what I would like is to be able to produce a scatter plot of
the observed oucomes or the estimates, in my case Fisher's z for the x axis
and the standard error in the y axis, with the standard error  (SE) the
same as it appears when running the funnel() function for a funnel plot
with the model (without moderators) as the input argument. Actually, it is
a funnel plot without the background of the funnel distribution but just
the scatter of points, that is suppressing the funnel distribution on
the background.

I tried to do so in agreement with the definition of SE used for the funnel
plot in the package Vignette published at Journal of Scientific software in
page 26:

"*For models without moderators, the figure shows the observed outcomes on
the horizontal axis against their corresponding standard errors (i.e., the
square root of the sampling variances) on the vertical axis. A vertical
line indicates the **estimate based on the model. A pseudo confidence
interval region is drawn around this value with bounds equal to ±1.96 · SE,
where SE is the standard error value from the vertical axis.*"


I tried to reproduce the vertical axis (y) using the square root of the
sampling variable, but the result was an upside down scaling of the
observed outcomes or estimates on a different y scale for the x ticks. The
plot seems to have similarities with the funnel plot from the funnel()
function, but it is not exactly the same without the background of the
funnel distribution graphic. Maybe the problem could be that in the
funnel() function, contrary to my simple attempt to imitate it with the
square root of the sampling variable, the pseudo confidence interval is
estimated for each value? Could this be the reason?


If so, how could I reproduce the funnel () function plot without the funnel
distribution graphic in the background and just the scattering of the
points using the same pseudo-confidence interval?


Thanks a lot for your help and assistance.

Kind regards,

Gabriel

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