Interaction between random and fixed effects

Dear Thierry,

Thank you for your response.
Local is coded with the name of the local, but I believe the nesting is
implicit in the data.

with(dataset, isNested(as.character(Local), as.character(Year)))
returns TRUE

The example is attached.

Best wishes,

Vin?cius

Em seg., 31 de mai. de 2021 ?s 16:10, Thierry Onkelinx <
thierry.onkelinx at inbo.be> escreveu:

Dear Vinicius,

What did you ran the interaction as a fixed effect Year:Local or a
random effect (1|Year:Local)?  How did you code Local: as a unique value
for every Local and Year combinations? Please do share output or a minimal
example so we know exactly what you did. I'm still a novice at mind reading.

Best regards,

ir. Thierry Onkelinx
Statisticus / Statistician

Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE
AND FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkelinx at inbo.be
Havenlaan 88 bus 73, 1000 Brussel
www.inbo.be


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Op ma 31 mei 2021 om 20:57 schreef Vinicius Maia <
vinicius.a.maia77 at gmail.com>:

Hi all,

I have a subtle doubt in how to interpret the interaction between fixed
(or
even random) and random effects in the following case.

I have a model: Y ~ Year + (1|Local)+(1|Genotype) + (Year:Local:Genotype)
Year is a fixed effect because it has only 4 levels.

I ran the model with the random and fixed effect interaction just to
explore, but I was not expecting that it would work because Locals are
completely nested within Years.

To my surprise, the model ran and the variance of Year:Local:Genotype are
quite big. How is it possible to have Local interacting with Year if they
are nested? I also tried: Y ~ Year + (1|Local)+(1|Genotype) +
(Year:Local)
and the model rans too, without singular fit.

I am struggling to understand if random interactions (it also extends to
cases where the interactions are only between nested random effects) mean
that the variance between Locals changes with Years or if the effect of a
given Local changes with Years. If it is the former option I can
understand
why the model ran and has a high variance for the interaction, but if it
is
the later case (which I believe it is), how does the model estimate an
interaction for Local:Year if they are nested?

Thanks!

Best wishes,

Vin?cius Maia

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