[R-meta] Inner|outer model vs multiple random id terms in rma.mv

[Divya Ravichandar]

Hi all,

I am trying to understand why results from running a model of the form
~lvl1|lv2 are not comparable to results of running ~1 | lvl1 ,~ 1 | lvl2

In a simple example case below,results of the 2 models are comparable as
expected.

```case <- data.frame(Dataset=
c("a","b","c","d"),Cohort=c("c1","c1","c2","c3"), Tech=
c("a1","a2","a1","a1"),Effect_size=c(-1.5,-3,1.5,3),Standard_error=c(.2,.4,.2,.4))
res1 = rma.mv(Effect_size, Standard_error^2, random = list(~ 1 | Dataset,~
1 | Cohort), data=case)
res2=rma.mv(Effect_size, Standard_error^2, random = ~ Dataset | Cohort,
data=case)
```
However, when running the 2 model on a more complex example [attached]
markedly different results are obtained with ~ Dataset | Cohort estimating
a pvalue of .02 and list(~ 1 | Dataset,~ 1 | Cohort) estimating a pvalue of
.2
-- 
*Divya Ravichandar*
Scientist
Second Genome

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