[R-meta] metafor::matreg() and its workflow

[Viechtbauer, Wolfgang (SP)]

Dear Stefanou,

See below for my responses.

Best,
Wolfgang

>-----Original Message-----
>From: Stefanou Revesz [mailto:stefanourevesz using gmail.com]
>Sent: Sunday, 05 December, 2021 3:55
>To: R meta; Viechtbauer, Wolfgang (SP)
>Subject: metafor::matreg() and its workflow
>
>Dear Wolfgang,
>
>In the latest version of metafor, I realized there are a couple of new
>functions specifically made for correlations (that's awesome!).
>
>I understand the use of rclac() which provides the V for rma.mv(). But
>I'm a bit unclear why we get the vcov() from the rma.mv() fit and then
>input it to matreg().
>
>My questions are:
>
>1- What role does matreg() play and why not just using rma.mv()?

matreg() is for fitting regression models based on variance-covariance and correlation matrices. Such a matrix can be obtained by conducting a meta-analysis (e.g., using rma.mv()). This all takes us into methodology that is sometimes described as MASEM (meta-analytic structural equation modeling). Maybe start with this chapter:

Becker, B. J., & Aloe, A. (2019). Model-based meta-analysis and related approaches. In H. Cooper, L. V. Hedges, & J. C. Valentine (Eds.), The handbook of research synthesis and meta-analysis (3rd ed., pp. 339-363). New York: Russell Sage Foundation.

to go along with:

https://wviechtb.github.io/metafor/reference/matreg.html

and

https://wviechtb.github.io/meta_analysis_books/cooper2019.html#16)_Model-Based_Meta-Analysis_and_Related_Approaches

>3- What if our rma.mv() fit has multiple (interactive) moderators,
>what should be passed as R and vcov() to matreg()?

I can't really answer this question without further details. But I would suggest to first read up on the methdology itself.

>3- Is rtoz =TRUE necessary in this workflow?

I assume you mean argument 'ztor' in matreg(). Whether to use this depends on whether you have a matrix of r-to-z transformed correlation coefficients or a matrix of raw correlation coefficients. Whether one should or should not use transformed correlations in a meta-analysis that could yield such a matrix is a lengthy and endless debate, so I am not going to touch on "necessary" without a ten-foot pole.

>Thank you,
>Stefanou