[R-meta] including uninformative levels
||@t@ @end|ng |rom dewey@myzen@co@uk
Fri Dec 3 18:11:27 CET 2021
In general, in regression, if you have a level in one of the factors
which is represented by a single observation then that observation will
be perfectly fitted and that observation will have high leverage.
In a random-effects model since it should contribute to the between
study variation then it would affect all the estimates since the weights
are dependent on the estimate of tau^2.
On 03/12/2021 13:29, Cátia Ferreira De Oliveira wrote:
> I hope you are well.
> Is there any benefit/disadvantage of including levels in your model that
> only have information coming from a single study? I always remove the
> intercept and do not include it in the follow-up comparisons between levels
> but wonder if there's a consequence to doing it this way since this one
> study will potentially introduce more heterogeneity and does not add much
> empirical value for this particular analysis.
> Best wishes,
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