[R-meta] Does clubSandwich::coef_test() handle crossed random-effects?

[James Pustejovsky]

I don't know what "directly and immediately" means. I mean clusters where
the sampling errors (or errors of estimation), defined as the difference
between the effect size estimate and its target parameter, are correlated.

James

On Wed, Oct 6, 2021 at 9:26 PM Farzad Keyhan <f.keyhaniha using gmail.com> wrote:

> Many thanks, you mean the cluster that "directly and immediately" contains
> the true and subsequently overlapping observed effects, not the ones higher
> up in the hierarchy, that is the logic, correct?
>
> Fred
>
> On Wed, Oct 6, 2021 at 9:21 PM James Pustejovsky <jepusto using gmail.com>
> wrote:
>
>> Hi Fred,
>> The cluster argument in impute_covariance_matrix describes sets of effect
>> sizes that you expect to have correlated sampling errors, which arise if
>> multiple effect sizes are estimated from a common sample (or from partially
>> overlapping samples). So in your case, use cluster = study.
>> James
>>
>> On Wed, Oct 6, 2021 at 9:03 PM Farzad Keyhan <f.keyhaniha using gmail.com>
>> wrote:
>>
>>> Dear James,
>>>
>>> One quick question, (recall I have 'scales' subsuming 'studies'
>>> subsuming 'true effects'). In this case, to set up a V matrix, should I use
>>> 'study' as or 'scale' to define the 'cluster' argument in
>>> 'impute_covariance_matrix()'?
>>>
>>> Thanks,
>>> Fred
>>>
>>> On Sun, Oct 3, 2021 at 9:25 PM Farzad Keyhan <f.keyhaniha using gmail.com>
>>> wrote:
>>>
>>>> Dear James,
>>>>
>>>> I explored the issue, there was a re-coding bug. One thing that I
>>>> wanted to clarify is that in addition to the 'scale > study' nesting
>>>> relationship, the same 'scale' was used to measure different 'outcomes' and
>>>> different 'scales' can be used to measure the same 'outcome' across the
>>>> studies.
>>>>
>>>> Do you see any potential for crossed random-effects here?
>>>> (data attached for clarity)
>>>>
>>>> Fred
>>>>
>>>> dat <- read.csv("https://raw.githubusercontent.com/ilzl/i/master/j.csv
>>>> ")
>>>>
>>>>   study scale       yi        vi es group outcome time
>>>> 1    A1    p1 1.680746 0.2081713  1     1       3    0
>>>> 2    A1    p1 4.122057 0.4806029  2     2       3    0
>>>> 3    A1    p1 2.600443 0.2838905  3     1       3    1
>>>> 4    A1    p1 3.457194 0.3836960  4     2       3    1
>>>> 5    A1    p1 1.546293 0.1998273  5     1       3    2
>>>> 6    A1    p1 3.071523 0.3352741  6     2       3    2
>>>>
>>>> On Sun, Oct 3, 2021 at 6:59 PM James Pustejovsky <jepusto using gmail.com>
>>>> wrote:
>>>>
>>>>> On Sun, Oct 3, 2021 at 1:18 PM Farzad Keyhan <f.keyhaniha using gmail.com>
>>>>> wrote:
>>>>>
>>>>>> I see, I'm still exploring to see what has caused the two models in
>>>>>> my previous email to give slightly different fits. Still curious though,
>>>>>> for 'scale' and 'study' to have been crossed random effects, 'scale' should
>>>>>> have varied in each study?
>>>>>>
>>>>>
>>>>> Yes.
>>>>>
>>>>

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