[R-meta] combining Means + SD at post, withD + 95% CI

[Jorge Teixeira]

 Dear Michael, thank you - that is indeed more elegant.

Out of curiosity, is it possible to do this in “meta” package too?

Michael Dewey <lists using dewey.myzen.co.uk> escreveu no dia segunda, 27/03/2023
à(s) 13:32:

> Dear Jorge
>
> I think the conv.wald() function in metafor will calculate the variance
> for you. You do need an up-to-date version of metafor.
>
> Michael
>
> On 26/03/2023 21:28, Jorge Teixeira via R-sig-meta-analysis wrote:
> >   Hi all.
> >
> > I did this to combine studies that provided M+SD, with others for which I
> > had only MD + 95% CI or p-value.
> >
> >
> > *Questions: *
> >
> > i)   Is the Vi well calculated below, as the code was given by GPT?  n
> per
> > group is irrelevant here, right?
> >
> > ii)  Is there a more elegant way to do this?
> >
> > iii) Can this method backfire in some way or is there something in
> > particular that I should have in mind?
> >
> >
> > Thanks! Code below:
> >
> > library(metafor)
> >
> > #
> > dat <- structure(list(study = c("AA", "BB", "CC",
> >                                  "EE", "DDD"), en = c(9, 41, 29, 8, 13
> >                                  ), em = c(32, 27.5, 28.7, 22.8, 30.5),
> esd
> > = c(1.9, 3.8, 5.2,
> >
> >     3.8, 4.9), cn = c(8, 26, 28, 10, 14), cm = c(30.1, 24.9, 26.9,
> >
> >                                                  24.7, 30.2), csd =
> c(2.4,
> > 3.6, 3, 4.3, 5.1)), row.names = c(NA,
> >
> >
> >                                  -5L), class = c("tbl_df", "tbl",
> > "data.frame"))
> >
> > #
> > dat <- escalc(measure="MD", m1i=em, sd1i=esd, n1i=en, m2i=cm, sd2i=csd,
> > n2i=cn, data=dat)
> >
> >
> > # Now lets had study "XING", which has a MD of 8 (95%CI: 4, 12), n=60;
> > p=0.001
> >
> > sampling variance = (CI / 1.96) ^ 2 / (2 * sample size)
> >
> > (8 / 1.96) ^ 2 / (2 * 6) = 1.388
> >
> >
> > # Create a new row for study XING
> > new_row <- data.frame(study = "XING", en = NA, em = NA, esd = NA, cn =
> NA,
> > cm = NA, csd = NA, yi = 8, vi = 1.388)
> >
> > # Add the new row to dat
> > dat <- rbind(dat, new_row)
> >
> > #
> > res <- rma(yi, vi,  data=dat)
> > res
> >
> >       [[alternative HTML version deleted]]
> >
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>
> --
> Michael
> http://www.dewey.myzen.co.uk/home.html
>

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