Message-ID: <b144559ac0ca4fc69d3d5e70f66b242b@UM-MAIL3214.unimaas.nl>
Date: 2019-09-18T16:50:05Z
From: Wolfgang Viechtbauer
Subject: [R-meta] Moderator analysis test of residual heterogeneity confusion
In-Reply-To: <D2C70FAD-FE1E-4F10-AE0E-B59535D36A4E@my.fsu.edu>
Dear Mia,
Your screenshots did not come through properly. Note that this a text-only mailing list, so please post output, not screenshots. Also, please post in plain text -- not rich text format or HTML.
Best,
Wolfgang
-----Original Message-----
From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces at r-project.org] On Behalf Of Mia Daucourt
Sent: Wednesday, 18 September, 2019 18:24
To: r-sig-meta-analysis at r-project.org
Subject: [R-meta] Moderator analysis test of residual heterogeneity confusion
Good afternoon,
I am using the metafor package to run a multilevel correlated effects model. For moderator analyses, I am running them one at a time, to see how much heterogeneity each accounst for, and then I ran model with all mods to see how much variance is left to be explained they're combined.?
I have an odd a situation where there is?no?significant residual variance with just an individual moderator in the model, but then for a set of moderators (that includes that moderator) there?is?significant residual variance. How can this be?
Maybe these screenshots can help...
Single moderator results:
Moderator analysis test of residual heterogeneity confusion
All mods model results:
Thank you for your help!
My best,
Mia