[R-meta] Multivariate meta-analysis when "some studies" are multi-outcome

Tue, Mar 16, 2021 3:22 AM

Dear Simon,

At the very least, you should add random effects at the level of the studies and at the level of the estimates, so:

dat$estid <- 1:nrow(dat)

and then

random = ~ 1 | id / estid

For longitudinal data, one could also consider using some kind of autocorrelation structure for the estimates within studies. There are some examples here:

https://wviechtb.github.io/metafor/reference/dat.ishak2007.html
https://wviechtb.github.io/metafor/reference/dat.fine1993.html

clubSandwich::impute_covariance_matrix() also allows for the construction of a V matrix with an autocorrelation structure.

If the different outcomes are meaningfully related across studies (i.e., outcome '1' stands for the same thing across all studies), then one could also consider using an unstructured var-cov matrix with correlated random effects for outcomes within studies. This would be akin to:

https://www.metafor-project.org/doku.php/analyses:berkey1998

Best,
Wolfgang

-----Original Message-----
From: Simon Harmel [mailto:sim.harmel at gmail.com]
Sent: Monday, 15 March, 2021 17:31
To: Viechtbauer, Wolfgang (SP)
Cc: R meta
Subject: Re: [R-meta] Multivariate meta-analysis when "some studies" are multi-
outcome

Dear Prof. Viechtbauer,

Many thanks for your response. I found the following particularly helpful
(https://stat.ethz.ch/pipermail/r-sig-meta-analysis/2019-March/001484.html).

So, I went from my initial model: `rma.mv(d, V = SE^2, mods = ~factor(outcome)-1,
random= ~1|id, data = dat)`
to now:

`V <- clubSandwich::impute_covariance_matrix(vi = dat$SE^2, cluster = dat$id, r =
0.7)`
`rma.mv(d, V = V, mods = ~factor(outcome)-1, random= ~1|id, data = dat)`

However, what type of dependence is accounted for by the multilevel part (i.e.,
`random= ~1|id`), and what type of dependence is accounted for by including the
imputed variance-covariance matrix?

Specifically, in my data, all primary studies (n=52) are longitudinal, 15 of them
are multi-outcome, and almost all are multi-group treatments. Are all of these
types of dependence reasonably accounted for?

Many thanks for your consideration,
Simon

On Mon, Mar 15, 2021 at 6:54 AM Viechtbauer, Wolfgang (SP)
<wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:
Hi Simon,

I would suggest to search/browse the archives, as this kind of question has been
discussed at various points in the past. The archives can be found here:

https://stat.ethz.ch/pipermail/r-sig-meta-analysis/

There is no built-in search functionality for the archives, but one can restrict
search engines to conduct searches at particular sites. For example, if you do a
google search including

site:https://stat.ethz.ch/pipermail/r-sig-meta-analysis/

you should only get 'hits' from the mailing list archives. The same should work
with DuckDuckGo. Note sure about other engines.

Note that search engines index the archives at semi-regular intervals, so the most
recent posts will not show up this way, but those can be searched manually.

Best,
Wolfgang

-----Original Message-----
From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces at r-project.org] On
Behalf Of Simon Harmel
Sent: Saturday, 13 March, 2021 23:53
To: R meta
Subject: [R-meta] Multivariate meta-analysis when "some studies" are multi-

outcome

Dear All,

I'm conducting a meta-analysis where 15 out of 52 studies have used more
than one outcome variable. In addition, almost all studies include multiple
treatments.

A shortened version (i.e., without moderators) of our dataset appears below
(`*id`=study id; `d`=effect size; `SE` = standard error; `outcome`=outcome
variable index*).

I was wondering what would be the appropriate modeling options for such a
situation?

I appreciate your expertise and consideration,
Simon

*#-- R data and code:*
dat <- read.csv("https://raw.githubusercontent.com/hkil/m/master/tst.csv")

library(metafor)
rma.mv(d, V = SE^2, mods = ~factor(outcome)-1, random= ~1|id, data = dat)
## I'm assuming this would be an insufficient model

[R-meta] Multivariate meta-analysis when "some studies" are multi-outcome

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