[R-meta] random part in meta-regression vs. that in multilevel models
Jack Solomon
kj@j@o|omon @end|ng |rom gm@||@com
Wed Mar 17 22:01:01 CET 2021
Hello List Members,
**First, I have always thought it is illegitimate to add random-effects for
something that has not been estimated in the fixed part of the model. For
example:
`lme4::lmer(math ~ female*minority + (ses | sch.id), data = data)` is
illegitimate because `ses` has not been estimated in the fixed part.
But I frequently see multilevel meta-regression models where intercept is
dropped (~0+...) from the fixed part but at the same time it is added to
the random part. For example:
metafor::rma.mv(es ~ 0+outcome, V, random= ~1|id/outcome, data = data)
>>>>>> So, why is this ok in meta-regression?
**Second, I have always thought that `outcome` is treated as a categorical
predictor and thus appearing only to the **left** of `|`. For example:
lme4::lmer(es ~0+outcome + (0 + outcome | id), data = data)
But I frequently see multilevel meta-regression models where outcome is
treated as a categorical predictor AND a **grouping variable** thus
appearing only to the **right** of `|`. For example:
metafor::rma.mv(es ~ 0+outcome, V, random= ~1|id/outcome, data = data)
>>>>>> So, why is this ok in meta-regression?
Many thanks for your support,
Jack
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