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

Dear Gabriel,

The funnel() function accepts vectors for 'col' and 'pch'. So you could do:

ri <- c(0.5, 0.6, 0.7, 0.8, 0.9)
ni <- c(100,110,150,200,250)
dat <-escalc(measure = "ZCOR", ri = ri, ni = ni)
funnel_all <- rma.mv(yi,  vi,  data=dat)

grp <- c(1,2,1,1,2)
cols <- c("red","blue")
pchs <- c(19,15)
funnel(funnel_all, back=NA, level=0, refline=1, yaxis="seinv",
col=cols[grp], pch=pchs[grp])
grid()
abline(v=1, col="blue", lwd=2)

Best,
Wolfgang

-----Original Message-----
From: R-sig-meta-analysis <r-sig-meta-analysis-bounces at r-project.org>

On Behalf

Of Gabriel Cotlier via R-sig-meta-analysis
Sent: Tuesday, November 7, 2023 08:50
To: Dr. Gerta R?cker <gerta.ruecker at uniklinik-freiburg.de>
Cc: Gabriel Cotlier <gabiklm01 at gmail.com>; R Special Interest Group for

Meta-

Analysis <r-sig-meta-analysis at r-project.org>
Subject: Re: [R-meta] question on scatter plot of estimates (Fisher's Z)

against

the standard error

Hello all,
According to:
https://www.metafor-project.org/doku.php/plots:funnel_plot_variations I
think it could be the argument:

   - yaxis="seinv" for the inverse of the standard errors

Is what gives the 1/SE for each element in the vector of effect sizes in
the x-axis.

How can I "stand alone"?that would be outside the metafore package or not
using the funnel function?to plot the same scatterplot of effect sizes
(x-axis) against 1/SE (y-axis) in communion and a simple R scatter
plot?without the funnel background?and afterwards use it to further

cluster

by coloring or using shapes ("pch") the effect sizes according to

different

categorical variables in the data frame?

Thanks a lot for your help.
Kind regards,
Gabriel

On Tue, Nov 7, 2023 at 9:13?AM Gabriel Cotlier <gabiklm01 at gmail.com>

wrote:

Dear Greta and colleges,

As can be seen below, Greta has provided a nice solution to a problem I
could not solve before, which is to have as an output of metafor's

package

function funnel() for plotting the funnel plot without the background

of

the funnel itself, which I very slightly modified as follows:

###################
##
##.  CODE FUNNEL
##
###################

## data
ri <- c(0.5, 0.6, 0.7, 0.8, 0.9)
ni <- c(100,110,150,200,250)
dat <-escalc(measure = "ZCOR",  ri = ri, ni = ni)

## model
funnel_all <- rma.mv(yi,  vi,  data=dat)

## get max and min values for plot
#funnel_all$yi
#min(funnel_all$yi)
#max(funnel_all$yi)

## funnel plot
f1 <- funnel(funnel_all,
             back = "white",
             # shade = "white",
             yaxis = "seinv",
             level = 0,
             # ylim = c(1, 5),
             refline=0,
             main="my plot",
             ylab = "Presicion (1/SE)",
             xlim = c(0.53,1.5))
# shade = c("white", "gray55", "gray75"),
# refline = 0)
# bg = "grey")
# legend = TRUE)
#grid(NULL, NULL,lwd = 1.6)
abline(h=c(9.849, 11.316, 12.783, 14.249, 15.716 ), col="grey", lwd=1,
lty=3)
abline(v=1, col="blue", lwd=2)
abline(v=c( 0.6, 0.8, 1, 1.2, 1.4), col="grey", lwd=1, lty=3)

This has been a very efficient solution for my problem of getting

exactly

the same funnel plot as the result of the metafore package
function funnel() without the funnel as a background. However, now I am
facing the challenge of having plotted the same funnel plot as the
output from the metafor's funnel() function without the background but
without the option of clustering by coloring or giving different point
shapes to the effect szes (points in the funnel plot) according to a
categorical in my data frame. I assume?probably wrongly?that for this

task

I would have to reproduce the same funnel plot as is output from the

funnel

plot function in the metafore package without the funnel background,

as in

the code above, and use my data frame with the categorical variables to
color the points or give them different shapes and sizes using the
categorical variables in my data frame. Now the funnel plot function

plots

in the x-axis the effect sizes, something I can easily get from my data
frame, but in the y-axis it uses 1/standad error (or 1 / SD). The
problem is that, as far as I understand, the standard error (SE)
corresponds to the standard deviation, or the R function sd() which

gives

one value per input vector. Therefore, for some reason, plotting the

effect

sizes (a vector class numeric) in the x-axis and 1/sd(effect_sizes)

will

give me a number, not a vector of the same length as the effect sizes.

*Therefore, how could one reproduce the same funnel plot as in the
metafore function (without the funnel background, just a scatterplot)
with an x-axis composed of the vector of effect sizes and a y-axis with
another vector corresponding to 1/stands error (1/SE) of each element

in

the x-axis--If 1/SE is is equal to 1/sd(efect_sizes) which is a scaler

and

not a vector ?*

I think maybe this could be achieved somehow by giving, in the y-axis,

a

kind of *"element-wise 1/SE"* to each element in the x-axis; that would
be an value corresponding to 1/SE to each of the elements in the

vector of

effect sizes in the x-axis. Could this be the idea behind the funnel

plot

function with 1/SE on the y-axis?

If so, can this be somehow achieved following the example provided by
Greta below?

ri <- c(0.5, 0.6, 0.7, 0.8, 0.9)
ni <- c(100,110,150,200,250)
dat <-escalc(measure = "ZCOR",  ri = ri, ni = ni)

Thanks a lot for your help and guidance.
Kind regards,
Gabriel