[R-meta] Meta-analysis including multiple intervention arms
jepu@to @end|ng |rom gm@||@com
Sun Nov 15 16:13:58 CET 2020
It depends on the structure of the random effects (i.e., the “working model” in the RVE framework).
If one used a model with independent random effects for each ES estimate, then yes, increased heterogeneity would mean that the study with 2 effects receives more weight.
But the “correlated effects” working model has a study-level random effect, which hits all ES estimates within the study. In the case, the study ends up getting the appropriate amount of weight in the overall average.
> On Nov 15, 2020, at 8:34 AM, Guido Schwarzer <sc using imbi.uni-freiburg.de> wrote:
> Am 14.11.20 um 16:29 schrieb James Pustejovsky:
>> [...] Splitting the control sample size would over-correct, so that the study would end up with less weight than it should receive.
> Is this also true if you have a (very) large between-study variance?
> In such cases each estimate gets essentially the same weight in a meta-analysis which means that a study with two estimates gets twice the weight (not sure about this relationsship if using RVE).
> Best wishes
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