[R-sig-ME] sample size in glmer model

[Ben Bolker]

  It's going to depend on whether the parameters you're trying to
estimate are capturing processes that vary at the level of
participants or at the level of observations.  For example, if you
wanted to compare trends over time among groups of participants, each
measured multiple times (i.e. a random-slopes model with a
fixed-effect interaction between treatment and slope) you'd need to
consider the number of participants. (In a sense the answer to this
question goes back to the classical experimental design bestiaries of
nested vs randomized block vs split-plot vs ... and deciding what the
"denominator degrees of freedom" are supposed to be in each case/for
each test of interest).

On Wed, Jan 22, 2020 at 9:45 AM Thierry Onkelinx via
R-sig-mixed-models <r-sig-mixed-models using r-project.org> wrote:
>
> Dear Sou,
>
> I'd suggest at least 10-15 observation per **parameter**. Categorical
> variables with more than two levels require more than one parameter. An
> interaction between two continuous variable requires 3 parameters (2 main
> effect + 1 interaction). Don't forget to count the hyperparameters of the
> random effects.
>
> Best regards,
>
> Thierry
>
> ir. Thierry Onkelinx
> Statisticus / Statistician
>
> Vlaamse Overheid / Government of Flanders
> INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
> FOREST
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>
> Op wo 22 jan. 2020 om 14:55 schreef Souheyla GHEBGHOUB <
> souheyla.ghebghoub using gmail.com>:
>
> > Hi,
> > In Field (2012) we need 10-15 *participants* per variable for regression,
> > in Levshina (2015) we need 10-15 *observations* per variable.
> >
> > Is it participant or observation? I am so confused as I have 53
> > participants and 1484 observations.
> >
> > Thank you,
> > Sou
> > PhD in Education
> > University of York
> >
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