[R-meta] aggregate data continues outcomes
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 at r-project.org] On Behalf Of Homa Keshavarz Sent: Tuesday, 15 December, 2020 19:27 To: 'R?ver, Christian'; r-sig-meta-analysis at 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