[R-meta] Inverse weighting after estimation of VCOV

[pedros@c m@iii@g oii st@ii@u@i-m@rburg@de]

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