[R-meta] aggregate data continues outcomes

[Viechtbauer, Wolfgang (SP)]

Dear Homa,

Please post in plain text. Note how the formatting of the table is messed up when not doing so, making it difficult for people to read the table and provide help.

It would also help if you would provide the table in a way that it can be directly generated within R (e.g., using dput()). See the following links for how to create reproducible examples:

https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example
http://adv-r.had.co.nz/Reproducibility.html
https://cran.r-project.org/web/packages/reprex/vignettes/reprex-dos-and-donts.html

Not sure what effect size measure you intend to use. Standardized mean differences? If so, you will find an example and code that deals with this kind of data here:

http://www.metafor-project.org/doku.php/analyses:gleser2009#quantitative_response_variable

In essence, you need to compute the var-cov matrix of the two effects and then you can combine them with rma.mv(). If you provide the table in such a way that it can be directly generated within R, I can help further.

Best,
Wolfgang

>-----Original Message-----
>From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org]
>On Behalf Of Homa Keshavarz
>Sent: Tuesday, 15 December, 2020 19:27
>To: 'Röver, Christian'; r-sig-meta-analysis using r-project.org
>Subject: [R-meta] aggregate data continues outcomes
>
>I do appreciate it if you direct me how to aggregate the 2 groups below.
>This study has 3 arms, comparison between A , B, and C.
>Group 1: A compare to B
>Group 2: A compare to C
>I need to aggregate theses 2 groups
>
>
>	M	SD	N	M	DD	N
>Group1	1248.0	698.0	15	2381.0	1313.0	15
>Group2	1248.0	698.0	15	1878.0	720.0	15
>
>Many thanks in advance,
>Homa