[R-meta] [External] Re: 4-Level analysis in metafor

[Michael Dewey]

Going by the two examples you gave of datasources I assumed something 
different. I agree that is not a fixed effect.

On 05/03/2022 16:07, Harris, Jordan L wrote:
> Hi Michael,
> 
> I am fitting age as a moderator because my primary research question is 
> to see whether the effect size changes with age, I just did not send 
> along my meta-regression. As I see it, datasource would be a random 
> effect because there were 36 distinct datasources and each had different 
> age ranges (i.e., wave). If you think it would be important to consider 
> datasource as a fixed effect moderator, I will happily give it a chance, 
> I just am not sure about what that would mean theroetically.
> 
> Jordan
> ------------------------------------------------------------------------
> *From:* Michael Dewey <lists using dewey.myzen.co.uk>
> *Sent:* Saturday, March 5, 2022 7:25 AM
> *To:* Harris, Jordan L <jordan-l-harris using uiowa.edu>; 
> r-sig-meta-analysis using r-project.org <r-sig-meta-analysis using r-project.org>
> *Subject:* [External] Re: [R-meta] 4-Level analysis in metafor
> Dear Jordan
> 
> I know this is not what you asked but are you sure that all of those
> should be random effects? Do you not want to fit age as a fixed effect
> as a potential moderator? I also wonder about datasource.
> 
> Michael
> 
> On 04/03/2022 16:29, Harris, Jordan L wrote:
>> Hi all,
>> 
>> Does rma.mv appropriately account for between- and within-cluster variance for 4 level nested data?
>> 
>> rma.mv(yi=ES, V=sampling_variance, slab=authors, data=Data, random = list(~ 1 | datasource_id/wave_id/study), tdist=TRUE, method="REML")
>> 
>> study_id = included study
>> datasource = the source of data (e.g., large cohort study or independent samples)
>> wave_id = the wave of the datasource (i.e., age) from which the study was analyzed
>> 
>> Multiple effect sizes can occur at a given wave in a given data source. Multiple effect sizes also exist in a given study at a given wave. Provided this information, it might be important to nest studies within waves within data sources. I ask because I see  that the sigma^2.2. estimate of my output is nearly 0 and I was not 
> sure if this is an accurate reflection of my data or metafor's ability 
> to account for differences at this added level? Should I use the 0 
> estimate at 2.2 to justify a removal of wave_id from the nesting?
>> 
>> Multivariate Meta-Analysis Model (k = 100; method: REML)
>> 
>> Variance Components:
>> 
>>              estim    sqrt  nlvls  fixed                          factor
>> sigma^2.1  0.0069  0.0832     41     no                   datasource_id
>> sigma^2.2  0.0000  0.0000     60     no           datasource_id/wave_id
>> sigma^2.3  0.0023  0.0482     82     no  datasource_id/wave_id/study_id
>> 
>> I am a graduate student, and I am new to meta-analyses, and I would love any feedback!
>> Thanks,
>> Jordan
>> 
>>        [[alternative HTML version deleted]]
>> 
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> 
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> Michael
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