[R-sig-ME] Interaction between random and fixed effects

Vinicius Maia v|n|c|u@@@@m@|@77 @end|ng |rom gm@||@com
Mon May 31 22:02:15 CEST 2021


Thank you a lot Thierry,

But besides that, is it sensical to estimate an interaction such as
local:year if local is nested within year? I believe it does not make sense
but when this model ran I started to question what I know.

Best wishes,

Vinícius



Em seg., 31 de mai. de 2021 às 16:52, Thierry Onkelinx <
thierry.onkelinx using inbo.be> escreveu:

> Dear Vinicius,
>
> I think the problem is with your response variable. It seems like you have
> a lot of observations with a response value a few orders of magnitude
> smaller than the global average. This grouping is not explained by any of
> the covariates in your model, leading to huge random effect BLUPs.
> Splitting the BLUPs over two variables probably yields a smaller penalty.
>
> Fitting the model with a log transformed response leads to a singular
> model with 0 variance for Local. This strengthens my belief that the
> problem is with the data.
>
> 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 using inbo.be
> Havenlaan 88 bus 73, 1000 Brussel
> www.inbo.be
>
>
> ///////////////////////////////////////////////////////////////////////////////////////////
> To call in the statistician after the experiment is done may be no more
> than asking him to perform a post-mortem examination: he may be able to say
> what the experiment died of. ~ Sir Ronald Aylmer Fisher
> The plural of anecdote is not data. ~ Roger Brinner
> The combination of some data and an aching desire for an answer does not
> ensure that a reasonable answer can be extracted from a given body of data.
> ~ John Tukey
>
> ///////////////////////////////////////////////////////////////////////////////////////////
>
> <https://www.inbo.be>
>
>
> Op ma 31 mei 2021 om 21:21 schreef Vinicius Maia <
> vinicius.a.maia77 using gmail.com>:
>
>> 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,
>>
>> Vinícius
>>
>> Em seg., 31 de mai. de 2021 às 16:10, Thierry Onkelinx <
>> thierry.onkelinx using 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 using inbo.be
>>> Havenlaan 88 bus 73, 1000 Brussel
>>> www.inbo.be
>>>
>>>
>>> ///////////////////////////////////////////////////////////////////////////////////////////
>>> To call in the statistician after the experiment is done may be no more
>>> than asking him to perform a post-mortem examination: he may be able to say
>>> what the experiment died of. ~ Sir Ronald Aylmer Fisher
>>> The plural of anecdote is not data. ~ Roger Brinner
>>> The combination of some data and an aching desire for an answer does not
>>> ensure that a reasonable answer can be extracted from a given body of data.
>>> ~ John Tukey
>>>
>>> ///////////////////////////////////////////////////////////////////////////////////////////
>>>
>>> <https://www.inbo.be>
>>>
>>>
>>> Op ma 31 mei 2021 om 20:57 schreef Vinicius Maia <
>>> vinicius.a.maia77 using 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,
>>>>
>>>> Vinícius Maia
>>>>
>>>>         [[alternative HTML version deleted]]
>>>>
>>>> _______________________________________________
>>>> R-sig-mixed-models using r-project.org mailing list
>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>>>
>>>

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