Message-ID: <SN6PR02MB55683C24CDD1762254378DB1F7CC0@SN6PR02MB5568.namprd02.prod.outlook.com>
Date: 2020-12-09T17:57:20Z
From: Ju Lee
Subject: [R-meta] Dear Wolfgang
Dear Wolfgang,
I hope you are well these days.
I had some general questions related to the data structure in mixed-effect models.
We are currently working with data extracted from pee-reviewed papers as well as big data extracted from state or agency surveys.
The issue we have is although we are including only 2-3 agency studies, each study can generate up to 1000-9000 effect sizes due to the abundance of data they produced.
Conversely, the data collected from peer-reviewed articles are much smaller than that perhaps < 800 effect sizes combined. My co-authors want to use those agency data, but I am very concerned that including those data makes sense.
So the question is:
1. Is it even reasonable to consider including such few studies that will pretty much dominate the entire data?
2. Can common mixed-effect model approaches with study random factor account for such disproportionate contribution of few studies?
It would be extremely helpful to hear your perspectives.
Thank you
Best,
JU
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