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Lets say I want to take the usual funnel plot for meta-analysis, and add another dimension to it, visually changing the points used for each study by a covariate. While it might be easier to change the marker or color for categorical variables, for a continuous variable, this gets a little harder.

Lets say we want to see if there's obvious asymmetry not just overall, but by say, length of follow-up. Does anyone know a way in either R or Stata to either change the size of the points plotted - so you essentially have a funnel-bubble plot, or to color them on a continuous gradient?

Clearly, this can be done by just modifying a scatterplot, but I'd like to save the steps in manipulating the access to get it looking like a conventional funnel plot.

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1 Answer 1

up vote 7 down vote accepted

You can do that with the funnel() function from the metafor package. Here is an example:

library(metafor)

data(dat.bcg)
res <- rma(ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg, measure="RR", method="REML")

ablat.scaled <- with(dat.bcg, (ablat - min(ablat))/(max(ablat) - min(ablat)))
ablat.scaled <- ablat.scaled * 2 + 0.5

funnel(res, cex=ablat.scaled)

Resulting figure shown below. Adapt to your taste.

funnel plot with asymmetrical point sizes

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Outstanding! Two questions - is there any chance you can go through what the code does a little bit? I confess R is still a touch...opaque to me. Secondarily, can metafor calculate measures of funnel plot asymmetry using those weighted points? –  Fomite Sep 12 '11 at 23:52
    
Answering my own question, it appears that metafor can handle modifying factors (like whatever the points are scaled by) as part of a regression test of funnel plot asymmetry. Could you confirm my understanding is correct? –  Fomite Sep 13 '11 at 3:19
    
Regarding what the code does: data(dat.bcg) to load the dat.bcg dataset. With res <- rma(...), I am fitting a random-effects model, specifying the counts of the 4 cells of the 2x2 tables in the studies. I set measure="RR" so that the (log) relative risk is used as the outcome measure for the meta-analysis. In the next two lines, I just take some variable and rescale it so that the smallest value is 0.5 and the largest 2.5. This gives me something that I can supply to the cex argument to indicate the point sizes. –  Wolfgang Sep 13 '11 at 21:51
    
Regarding measures of funnel plot asymmetry: You can do the regression and rank correlation test (functions regtest and ranktest). The regression test allows you to specify a model that already includes one or more covariates/moderators (such as length of follow-up). –  Wolfgang Sep 13 '11 at 21:56
    
Thanks again :) –  Fomite Sep 13 '11 at 22:44

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