[R-sig-ME] glmmTMB: testing for temporal variation in effect of fixed predictor on response variable

Thierry Onkelinx thierry@onkelinx @ending from inbo@be
Wed Nov 7 10:34:47 CET 2018

Dear Brenna,

Adding a random effect (1|year:fixed) makes sense, assuming that both year
and fixed are discrete. Note that adding this allows for a very liberal
temporal variantion by the fixed effect. Each level of the interaction is
independent from all other levels.

Best regards,

ir. Thierry Onkelinx
Statisticus / Statistician

Vlaamse Overheid / Government of Flanders
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkelinx using inbo.be
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what the experiment died of. ~ Sir Ronald Aylmer Fisher
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ensure that a reasonable answer can be extracted from a given body of data.
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Op wo 7 nov. 2018 om 00:16 schreef Brenna Levine <levine.brenna.a using gmail.com

> Dr. Bolker,
> I'm hoping that I might be able to bother you with a quick question. I am
> trying to *test whether there is significant temporal variation in the
> effect of a fixed predictor on my response variable *with a model in which
> year is specified as a random effect (I have 20 years of data). Currently,
> I am doing this by fitting an interaction between the fixed effect and the
> random effect of year as* (1|year:fixed)* (per a recommendation that I saw
> on RSeek.org at some point and some tips that I have read on this
> list-serve), and am testing the significance of this random interaction
> with a LRT (i.e., with a model lacking this interaction).
> Could you tell me if (a) (1|year:fixed) is the correct way to specify this,
> and (b) if not, do you have a recommendation for how I should specify this
> interaction to test for temporal variation in the effect of a fixed
> predictor on my response variable?
> Thanks.
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