-----Original Message-----
From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces at r-project.org] On
Behalf Of Filippo Gambarota
Sent: Monday, 03 January, 2022 16:42
To: R meta
Subject: [R-meta] fixed-effect multivariate model interpretation
Hello!
I'm fitting for the first time a multivariate fixed-effect model using
metafor. The code is:
```
rma.mv(yi, V, mods = ~ 0 + outcome, data = data, test = "t")
```
Where V is the block variance-covariance matrix created with vcalc()
that represents the covariance between different outcome levels within
each study. The outcome is a factor that represents different effect
sizes measured on the same participants within a study.
The model as expected did not estimate tau for each outcome and test
all coefficients (each outcome mean with this parametrization) against
0 (both the omnibus test and each beta). My question is about the
*residual heterogeneity* parameter and the associated Q test. Under
this model, I should have assumed that there is no heterogeneity
within each outcome level so I'm not sure how to interpret the
residual heterogeneity in this case.
Thank you!
Filippo
--
Filippo Gambarota
PhD Student - University of Padova
Department of Developmental and Social Psychology
Website: filippogambarota.netlify.app
Research Group: Colab Psicostat