[R-meta] "Favours experimental/vaccinated", "Favours control" - Metafor

[Viechtbauer, Wolfgang (NP)]

Dear Andrzej,

In this example, the 2x2 table is of the form as shown here:

https://wviechtb.github.io/metadat/reference/dat.bcg.html#details-1

Since a low 'TB positive' count is desirable, a negative log risk ratio therefore indicates that the results of a study favor the vaccinated group.

But one could just as well have computed the log risk ratios with:

dat <- escalc(measure="RR", ai=cpos, bi=cneg,
                            ci=tpos, ti=tneg, data=dat)

In this case, a positive log risk ratio would indicate that the results favor the vaccinated group.

So, one really has to understand what is being computed and whether positive or negative values indicate which group is being favored.

Best,
Wolfgang

> -----Original Message-----
> From: R-sig-meta-analysis <r-sig-meta-analysis-bounces using r-project.org> On Behalf
> Of Andrzej Andrzej via R-sig-meta-analysis
> Sent: Sunday, October 29, 2023 18:25
> To: Michael Dewey <lists using dewey.myzen.co.uk>
> Cc: Andrzej Andrzej <xaf3111.developers using gmail.com>; R Special Interest Group for
> Meta-Analysis <r-sig-meta-analysis using r-project.org>
> Subject: Re: [R-meta] "Favours experimental/vaccinated", "Favours control" -
> Metafor
>
> Thank you Michael,
> Yes, I do not know how to quote here, but I try:
> 1. "Do you mean whether to type   c("Favors control","Favors experimental")
> or  c("Favors experimental", "Favors control")?"
> Yes, exactly I do mean that.
>
> 2. "If so the answer is that when you computed the effect size you knew
> whetheh high values favoured experimental and so would be on the right
> of the plot (the first option) or vice versa"
> Could you please guide me with explanation based on this code and WV data,
> please:
> https://wviechtb.github.io/metadat/reference/dat.bcg.html
>
> library(metafor)
> data(dat.bcg)
> dat <- dat.bcg
>
> ### calculate log risk ratios and corresponding sampling variances
> dat <- escalc(measure="RR", ai=tpos, bi=tneg,
>                             ci=cpos, di=cneg, data=dat,
>                             slab=paste0(author, ", ", year))
> ### random-effects model
> res <- rma(yi, vi, data=dat)
> forest(res, addpred=TRUE, xlim=c(-16,7), at=seq(-3,2,by=1), shade="zebra",
>        ilab=cbind(tpos, tneg, cpos, cneg), ilab.xpos=c(-9.5,-8,-6,-4.5),
>        cex=0.75, header="Author(s) and Year")
> text(c(-9.5,-8,-6,-4.5), res$k+2, c("TB+", "TB-", "TB+", "TB-"), cex=0.75,
> font=2)
> text(c(-8.75,-5.25),     res$k+3, c("Vaccinated", "Control"),    cex=0.75,
> font=2)
>
> 3. "whetheh high values favoured experimental and so would be on the right
> of the plot (the first option) or vice versa"
> Could you please explain using that forest plot and bcg.data, where are
> those higher values (in which group) so how should I label Log Risk Ratio X
> axis according to RevMan 5 style with " Favours control" and "Favours
> vaccinated" ? I want to understand which way is correct, please.
> best regards,
> Andrzej