[R-meta] Random-effect specification in rma.mv() for multiple sources?

[Michael Dewey]

Dear Tim

I will leave it to the experts to check your structure but one thing 
which immediately strikes me is that you are going to need a very large 
dataset to be able to estimate all those random effects with any 
precision especially the ones with limited replicates. If you do get the 
model to converge it would be mandatory to look at diagnostics like the 
profile likelihoods.

Michael

On 29/06/2021 03:39, Timothy MacKenzie wrote:
> Dear all,
> 
> I noticed some errors in the copy-pasted data structure in my previous post
> (https://stat.ethz.ch/pipermail/r-sig-meta-analysis/2021-June/002953.html).
> Below is my correct data structure. From left to right, one can see the
> hierachical structure in my dataset:   study > sample > outcome > time >
> control > obs
> 
> Q:  Would the following random-effect structure account for all the above
> sources (as a first step to then drop the ones that are insignificant)?
> 
> random = list(~ sample | study, ~ time | interaction(study,sample,outcome),
> ~ 1 | control, ~ 1 | obs)
> 
> Thanks, Tim
> 
> study  sample  outcome time  control obs
> 1      1       1       1     1       1
> 1      1       2       1     1       2
> 1      1       1       2     1       3
> 1      1       2       2     1       4
> 1      2       1       1     1       5
> 1      2       2       1     1       6
> 1      2       1       2     1       7
> 1      2       2       2     1       8
> 2      1       1       2     1       9
> 2      1       2       2     1       10
> 2      1       1       2     2       11
> 2      1       2       2     2       12
> 3      1       1       3     1       13
> 3      1       1       3     2       14
> 3      2       1       3     1       15
> 3      2       1       3     2       16
> 
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-- 
Michael
http://www.dewey.myzen.co.uk/home.html