[R-meta] including uninformative levels

Cátia Ferreira De Oliveira cm|o500 @end|ng |rom york@@c@uk
Fri Dec 3 18:13:41 CET 2021

Thank you for your response. So it would be better to just remove that for
that level then.

Best wishes,


On Fri, 3 Dec 2021 at 17:11, Michael Dewey <lists using dewey.myzen.co.uk> wrote:

> Dear Cátia
> 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.
> Michael
> On 03/12/2021 13:29, Cátia Ferreira De Oliveira wrote:
> > Hello,
> >
> > 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,
> >
> > Catia
> >
> --
> Michael
> http://www.dewey.myzen.co.uk/home.html

Cátia Margarida Ferreira de Oliveira
Psychology PhD Student
Department of Psychology, Room A105
University of York, YO10 5DD
Twitter: @CatiaMOliveira
pronouns: she, her

	[[alternative HTML version deleted]]

More information about the R-sig-meta-analysis mailing list