[R-meta] Guidance for interpreting fixed effects in multilevel models

Simon Harmel @|m@h@rme| @end|ng |rom gm@||@com
Mon Aug 9 05:12:33 CEST 2021

Dear Colleagues,

I want to use two multilevel meta-regression models (below), but was
wondering what the correct interpretation of my fixed effects in each one
is? (given that the models' random effects are different).

In both models, *time* is a factor ranging from 0 to 4;  *ktype* is a
factor (0=direct,1=indirect) that can vary between studies and between
groups in each study (but not between outcomes and time points nested
within those groups in each study);  and *treat* is a study-level
continuous variable (# of treatments in each study).

Model 1: rma.mv(yi ~ 0 + time + ktype + treat, random = list(~ ktype |
study, ~time | interaction(study, group, outcome), ~1 | esID),struct =

Model 2: rma.mv(yi ~ 0 + time + ktype + treat, random =  list(~ ktype |
interaction(study,group,outcome), ~time | study, ~1 | esID), struct =

I highly appreciate your expertise and assistance,

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