[R-meta] Redundant predictors
Viechtbauer, Wolfgang (SP)
wo||g@ng@v|echtb@uer @end|ng |rom m@@@tr|chtun|ver@|ty@n|
Mon Feb 4 16:58:39 CET 2019
I would have to see your data/model, but yes, if the model matrix is not of full rank (which could be because certain combinations of two factors do not occur in a model that allows the two factors to interact), then rma.mv() will drop predictors so the model matrix is of full rank. Here is an example with two factors:
yi <- rnorm(9)
F. <- factor(c("a","a","a","b","b","b","c","c","c"))
G. <- factor(c("1","2","2","1","2","2","1","1","1"))
vi <- rep(1, 9)
rma.mv(yi, vi, mods = ~ F.*G.)
Note that the combination c-2 never occurs. So, the interaction term for this term is dropped from the model.
Is this a problem? Well, it does mean that we cannot estimate certain coefficients. In the example above, we cannot test whether the difference between F.c and F.a is different for the two levels of factor G (essentially, the difference between F.c and F.a is assumed to be the same for both levels of factor G, that is, 0.6451). But this aside, the model is still ok.
From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org] On Behalf Of Arne Janssen
Sent: Monday, 04 February, 2019 16:16
To: 'r-sig-meta-analysis using r-project.org'
Subject: [R-meta] Redundant predictors
I am running an rma.rv with two categorical and one continuous moderator
plus their interactions. Analysis of the full model give a Warning
message: In rma.mv ( ...) : Redundant predictors dropped from the model.
Based on the model output, I guess this is caused by the absence of all
combinations of the two categorical moderators, is that correct? If so,
is this something to worry about?
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