[R-meta] Inverse weighting after estimation of VCOV

[James Pustejovsky]

Hi David,

I don't entirely understand the models that you're looking at, so
clarifying the following would help in getting good feedback:
* What is the variable `shared_variance` used in the vcalc call?
* What is the variable `number` used in the random effects argument of
rma.mv?
* How are these variables related?

Additionally, it would be good to check that the vcov matrix created by
vcalc() is as you intend it to be. Could you pull out the blocks of this
matrix for a few studies and just verify that they give you covariance
matrices with a correlation of 0.7? I mean something like:
vcov_study_k <- V_mat[i:j, i:j]
cov2cor(vcov_study_k)
where the indices i:j are the rows in your data corresponding to a given
study k.

James

On Fri, May 24, 2024 at 10:00 AM David Pedrosa via R-sig-meta-analysis <
r-sig-meta-analysis using r-project.org> wrote:

> Dear all,
>
> I have a basic question about the output of my (gu)estimation of the
> variance-covariance matrix. I have extracted results from very
> heterogeneous studies with OR as effect size (sample sizes between 20
> and 300,000). Since some of the results come from the same study, I
> decided to try to use the VCOV as an input and estimated values
> according to the following formula
>
> V_mat  <- vcalc(vi=vi, cluster=shared_variance, data=df_complete, rho=.7)
> res_meta     <- rma.mv(yi, vi, V=V_mat,
>                          random = ~ 1 | number, mods = ~ hospitalbeds +
> ltcbeds, verbose=TRUE, data=df_complete)
>
>
> Interestingly, in this case the weighting is reversed, so that most of
> the weight is given to studies with the smallest sample size; something
> that does not happen when using this formula:
>
> res_meta     <- rma(yi, vi,
>                          random = ~ 1 | number, mods = ~ hospitalbeds +
> ltcbeds, verbose=TRUE, data=df_complete)
>
> I have tried to understand what is going on, but I am at kind of lost.
> Could someone please give me some advice?
>
> Thanks in advance,
>
> David
>
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