[R-meta] metafor::vcalc() for multiple sources of dependence

[Simon Harmel]

Thanks, Wolfgang. If I only intend to assume that the r_i for the same
repeatedly measured group on the same outcome, as well as on multiple
outcomes is constant (r_i = .6) and at the same time factor in the
shared control group, which arguments should be simultaneously used
for the Brown study below?

I did see the help page but wasn't able to find an example that was
similar to my study below.

Thank you,
Simon

m="
study yi vi group time outcome
Brown -0.10 0.05 1 0 1
Brown 0.24 0.05 1 0 2
Brown -0.11 0.05 1 0 3
Brown -0.01 0.05 1 0 4
Brown -0.12 0.05 2 0 1
Brown 0.38 0.05 2 0 2
Brown -0.19 0.05 2 0 3
Brown 0.30 0.05 2 0 4
Brown 0.45 0.05 1 1 1
Brown 0.66 0.05 1 1 2
Brown 0.27 0.05 1 1 3
Brown 0.13 0.05 1 1 4
Brown 0.08 0.05 1 2 1
Brown 0.25 0.05 1 2 2
Brown -0.34 0.05 1 2 3
Brown -0.06 0.05 1 2 4
Brown 0.48 0.05 2 1 1
Brown 0.28 0.05 2 1 2
Brown 0.10 0.05 2 1 3
Brown 0.25 0.05 2 1 4
Brown 0.11 0.05 2 2 1
Brown 0.65 0.05 2 2 2
Brown 0.39 0.05 2 2 3
Brown 0.13 0.05 2 2 4"

data <- read.table(text=m,h=T)

On Fri, Mar 4, 2022 at 4:45 AM Viechtbauer, Wolfgang (SP)
<wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:
>
> Hi Simon,
>
> Yes, that's what vcalc() is for.
>
> Best,
> Wolfgang
>
> >-----Original Message-----
> >From: Simon Harmel [mailto:sim.harmel using gmail.com]
> >Sent: Thursday, 03 March, 2022 17:35
> >To: Viechtbauer, Wolfgang (SP); R meta
> >Subject: metafor::vcalc() for multiple sources of dependence
> >
> >Hello Wolfgang,
> >
> >Thank you for adding such an important function! In my studies, I have
> >quite a few studies that are structured as shown below.
> >
> >Can I use vcalc() to construct a V matrix for the three sources of
> >dependence (i.e., multiple groups, times, outcomes) in say the study
> >below?
> >
> >Thank you for your guidance,
> >Simon
> >
> >m="
> >study yi vi group time outcome
> >Brown -0.10 0.05 1 0 1
> >Brown 0.24 0.05 1 0 2
> >Brown -0.11 0.05 1 0 3
> >Brown -0.01 0.05 1 0 4
> >Brown -0.12 0.05 2 0 1
> >Brown 0.38 0.05 2 0 2
> >Brown -0.19 0.05 2 0 3
> >Brown 0.30 0.05 2 0 4
> >Brown 0.45 0.05 1 1 1
> >Brown 0.66 0.05 1 1 2
> >Brown 0.27 0.05 1 1 3
> >Brown 0.13 0.05 1 1 4
> >Brown 0.08 0.05 1 2 1
> >Brown 0.25 0.05 1 2 2
> >Brown -0.34 0.05 1 2 3
> >Brown -0.06 0.05 1 2 4
> >Brown 0.48 0.05 2 1 1
> >Brown 0.28 0.05 2 1 2
> >Brown 0.10 0.05 2 1 3
> >Brown 0.25 0.05 2 1 4
> >Brown 0.11 0.05 2 2 1
> >Brown 0.65 0.05 2 2 2
> >Brown 0.39 0.05 2 2 3
> >Brown 0.13 0.05 2 2 4"
> >
> >read.table(text=m,h=T)