[R-meta] Multivariate meta-analysis when "some studies" are multi-outcome
Dear Prof. Viechtbauer, Many thanks for your response. I found the following particularly helpful ( https://stat.ethz.ch/pipermail/r-sig-meta-analysis/2019-March/001484.html). So, I went from my initial model: `rma.mv(d, V = SE^2, mods = ~factor(outcome)-1, random= ~1|id, data = dat)` to now: `V <- clubSandwich::impute_covariance_matrix(vi = dat$SE^2, cluster = dat$id, r = 0.7)` `rma.mv(d, V = V, mods = ~factor(outcome)-1, random= ~1|id, data = dat)` However, what type of dependence is accounted for by the multilevel part (i.e., `random= ~1|id`), and what type of dependence is accounted for by including the imputed variance-covariance matrix? Specifically, in my data, all primary studies (n=52) are longitudinal, 15 of them are multi-outcome, and almost all are multi-group treatments. Are all of these types of dependence reasonably accounted for? Many thanks for your consideration, Simon On Mon, Mar 15, 2021 at 6:54 AM Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:
Hi Simon, I would suggest to search/browse the archives, as this kind of question has been discussed at various points in the past. The archives can be found here: https://stat.ethz.ch/pipermail/r-sig-meta-analysis/ There is no built-in search functionality for the archives, but one can restrict search engines to conduct searches at particular sites. For example, if you do a google search including site:https://stat.ethz.ch/pipermail/r-sig-meta-analysis/ you should only get 'hits' from the mailing list archives. The same should work with DuckDuckGo. Note sure about other engines. Note that search engines index the archives at semi-regular intervals, so the most recent posts will not show up this way, but those can be searched manually. Best, Wolfgang
-----Original Message----- From: R-sig-meta-analysis [mailto:
r-sig-meta-analysis-bounces at r-project.org] On
Behalf Of Simon Harmel Sent: Saturday, 13 March, 2021 23:53 To: R meta Subject: [R-meta] Multivariate meta-analysis when "some studies" are
multi-outcome
Dear All, I'm conducting a meta-analysis where 15 out of 52 studies have used more than one outcome variable. In addition, almost all studies include
multiple
treatments. A shortened version (i.e., without moderators) of our dataset appears
below
(`*id`=study id; `d`=effect size; `SE` = standard error; `outcome`=outcome
variable index*).
I was wondering what would be the appropriate modeling options for such a
situation?
I appreciate your expertise and consideration,
Simon
*#-- R data and code:*
dat <- read.csv("https://raw.githubusercontent.com/hkil/m/master/tst.csv
")
library(metafor) rma.mv(d, V = SE^2, mods = ~factor(outcome)-1, random= ~1|id, data = dat) ## I'm assuming this would be an insufficient model