[R-sig-ME] 3-way interaction in random structure using gam

[Rudi Reiner]

Thank you very much Thierry!

Rudi

Am 25.05.2021 um 13:34 schrieb Thierry Onkelinx:
> Dear Rudi,
>
> Please keep the mailing list in cc.
>
> Yes. I'd use the model with only the 3-way interaction smoother. It 
> can handle all patterns of the lower interactions.
>
> 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 <mailto:thierry.onkelinx using inbo.be>
> Havenlaan 88 bus 73, 1000 Brussel
> www.inbo.be <http://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 di 25 mei 2021 om 13:30 schreef Rudi Reiner <rudi.reiner using boku.ac.at 
> <mailto:rudi.reiner using boku.ac.at>>:
>
>     Dear Thierry,
>
>     thank you for your reply. I am afraid, there was a typing error in
>     my initial message. Age and b.mass do have a non-linear (not lon
>     or log linear) relationship. Simplified, it may be a quadratic one
>     (see me model using lmer) but I think a gam would fit better. So
>     would you still suggest this model?:
>
>     gam(b.mass ~ te(age, area.forest, by = period), data = data,
>     random = list(pop=~1, year=~1))
>
>     Best regards,
>     Rudi
>
>     Am 25.05.2021 um 13:04 schrieb Thierry Onkelinx:
>>     Dear Rudi,
>>
>>     If age has a log-linear relationship, then use logAge as
>>     predictor rather than age.
>>
>>     I'm wondering why you insist on adding the 2-way interactions
>>     smoothers. You can't directly interpret 2-way interactions (or
>>     main effects) when you have a 3-way interaction that contains the
>>     same variables.
>>
>>     I'd simplify the model to gam(b.mass ~ te(log.age, area.forest,
>>     by = period), data = data, random = list(pop=~1, year=~1)).
>>
>>     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 <mailto:thierry.onkelinx using inbo.be>
>>     Havenlaan 88 bus 73, 1000 Brussel
>>     www.inbo.be <http://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 di 25 mei 2021 om 09:14 schreef Rudi Reiner
>>     <rudi.reiner using boku.ac.at <mailto:rudi.reiner using boku.ac.at>>:
>>
>>
>>         Hi there,
>>
>>         my actually trying to fit a non-linear mixed model (with a
>>         random
>>         structure) and am not sure how to do this correct using "gam"
>>         or "bam"
>>         from the mgcv package. My supervisor suggested me to ask R-sig.
>>
>>         My Data:
>>
>>         b.mass = body mass (continuous) - dependent variable
>>         _
>>         __predictor variables_
>>         age = continuous; lon-linear relationship with b.mass
>>         area.forest = continuous
>>         period =  factor; 2 levels
>>
>>         _random variables
>>         _year = continuous (1993-2019)
>>         pop = factor (28 different populations)
>>         --------------------------------------------------
>>
>>         First I fitted a linear model with quadratic age which seems
>>         to give me
>>         the "correct" results (biologically the results make sense).
>>         Especially
>>         I am interested in the 3-way interaction age x area.forest x
>>         period but
>>         also want/have to add all 2-way interactions:
>>
>>         */LM <- lmer(b.mass ~ ns(age,2)*area.forest*period + (1|pop)+
>>         (1|year),
>>         data = data)/*
>>
>>         Now I want to have the corresponding model using gam (or
>>         bam). I tried:
>>
>>         */gam <- gam(b.mass ~ period+s(age)+area.forest+s(age, by =
>>         area.forest)+s(age, by=period)+te(area.forest,
>>         by=period)+te(age,
>>         area.forest, by = period), data = data, random = list(pop=~1,
>>         year=~1))/*
>>
>>         The results (plot age~b.mass for different area.forest) look
>>         different
>>         to the lmer approach. Do have an idea, if my model (gam) is
>>         fitted
>>         correct, i.e., is it the "same" like the model I fitted using
>>         /`lmer`?/
>>
>>         Thank you,
>>         Rudi
>>
>>
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>>
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