Comparing mixed models

Dear Carlos,

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Caution: External email.

Thank you Jonh for you answer
I indeed used contr.sum, contr.poly before to model definition
after that I get the same results using any names for the same factors
but,?what do you exactly mean when testing for factors for differences 
over the origin?
The context here is models with both numeric and factor predictors. 
Consider a model of the form y ~ x*f, where x is numeric and f is a 
factor. A type-III test for the "main effect" of f tests for differences 
among factor levels where x = 0 (the origin).

More generally, the issues concerning "types" of tests in models with 
linear predictors are sufficiently complicated that discussing them in a 
help file or by email is likely to prove unsatisfactory. See the first 
two references in ?Anova for more details.

I hope this helps,
  John
best regards
Carlos

Em qua., 19 de jun. de 2024 ?s 10:14, John Fox <jfox at mcmaster.ca 
<mailto:jfox at mcmaster.ca>> escreveu:

    Dear Carlos,

     ?From ?Anova:

    "Warning

    Be careful of type-III tests: For a traditional multifactor ANOVA model
    with interactions, for example, these tests will normally only be
    sensible when using contrasts that, for different terms, are orthogonal
    in the row-basis of the model, such as those produced by contr.sum,
    contr.poly, or contr.helmert, but not by the default
    contr.treatment. In
    a model that contains factors, numeric covariates, and interactions,
    main-effect tests for factors will be for differences over the origin.
    In contrast (pun intended), type-II tests are invariant with respect to
    (full-rank) contrast coding. If you don't understand this issue, then
    you probably shouldn't use Anova for type-III tests."

    I hope this helps,
     ? John

    -- 
    John Fox, Professor Emeritus
    McMaster University
    Hamilton, Ontario, Canada
    web: https://www.john-fox.ca/ <https://www.john-fox.ca/>
    --
    On 2024-06-18 5:59 a.m., Carlos Barboza wrote:
     > [You don't often get email from carlosambarboza at gmail.com
    <mailto:carlosambarboza at gmail.com>. Learn why this is important at
    https://aka.ms/LearnAboutSenderIdentification
    <https://aka.ms/LearnAboutSenderIdentification> ]
     >
     > Caution: External email.
     >
     >
     > sorry, Anova type III function form car package in R
     >
     > Em ter., 18 de jun. de 2024 ?s 06:59, Carlos Barboza <
     > carlosambarboza at gmail.com <mailto:carlosambarboza at gmail.com>>
    escreveu:
     >
     >> Dear all,
     >> why Anova type III function gives different results if I change
    the names
     >> of a categorical factor? I suspect that is because contrast type
    but it's
     >> something strange get different results using the same data.
     >> thank you
     >>
     >> Em s?b., 7 de mai. de 2016 ?s 12:26, Carlos Barboza <
     >> carlosambarboza at gmail.com <mailto:carlosambarboza at gmail.com>>
    escreveu:
     >>
     >>> Dear Dr. Ben Bolker
     >>>
     >>> My name is Carlos Barboza and I am a Marine Biologist from the
    Rio de
     >>> Janeiro University, Brazil. First it's a pleasure to again have the
     >>> opportunity to send you a message.The reason for it is a simple
    doubt:
     >>> Can I compare AIC from:
     >>>
     >>> 1. glmmADMB: Density ~ 1 + 1|Site
     >>>
     >>> 2. glmmADMB: Density ~ Sector + 1|Site + Cage
     >>>
     >>> Note that they have different random and fixed structures. I
    know that
     >>> this is not the best choice to model selection but, I think
    that the AIC
     >>> values can be compared.
     >>>
     >>> thank you very much for your attention
     >>>
     >>>
     >>>? ? is Cage a random effect?? Are you intentionally leaving out the
     >>> intercept in the second case (it will be included anyway unless you
     >>> use -1)?? In any case, I don't see any obvious reason you can't
     >>> compare AIC values; see
     >>>
     >>>
    https://rawgit.com/bbolker/mixedmodels-misc/master/glmmFAQ.html#can-i-use-aic-for-mixed-models-how-do-i-count-the-number-of-degrees-of-freedom-for-a-random-effect <https://rawgit.com/bbolker/mixedmodels-misc/master/glmmFAQ.html#can-i-use-aic-for-mixed-models-how-do-i-count-the-number-of-degrees-of-freedom-for-a-random-effect>
     >>>
     >>>? ? Follow-ups to r-sig-mixed-models at r-project.org
    <mailto:r-sig-mixed-models at r-project.org>, please ...
     >>>
     >>> sorry, yes, cage was included only to examplify a different random
     >>> structure in the second case...it should be coded (1|Site) +
    (1|Cage)
     >>> yes, I know that the intercept will be included in the second model
     >>>
     >>> it's an example of comparing AIC values from mixed models with
    different
     >>> fixed and random structures:
     >>>
     >>> 1. Density ~ 1 + 1|Site
     >>>
     >>> 2. Density ~ Sector + 1|Site + 1|Cage
     >>>
     >>> comparing AIC...I beleive that both values can be compared
     >>>
     >>> again, thank you very much for your very fast message
     >>>
     >>>
     >>>
     >>>
     >>
     >> --
     >> Universidade Federal do Rio de Janeiro (UFRJ)
     >> Instituto de Biodiversidade e Sustentabilidade - NUPEM
     >> Caixa Postal 119331, CEP 27910-970
     >> Maca?, RJ, Brazil
     >> https://www.macae.ufrj.br/nupem/ <https://www.macae.ufrj.br/nupem/>
     >> http://lattes.cnpq.br/3629226944950076
    <http://lattes.cnpq.br/3629226944950076>
     >>
    https://scholar.google.com.br/citations?user=p-PRvd4AAAAJ&hl=pt-BR
    <https://scholar.google.com.br/citations?user=p-PRvd4AAAAJ&hl=pt-BR>
     >> https://www.researchgate.net/profile/Carlos_Barboza3
    <https://www.researchgate.net/profile/Carlos_Barboza3>
     >>
     >
     >
     > --
     > Universidade Federal do Rio de Janeiro (UFRJ)
     > Instituto de Biodiversidade e Sustentabilidade - NUPEM
     > Caixa Postal 119331, CEP 27910-970
     > Maca?, RJ, Brazil
     > https://www.macae.ufrj.br/nupem/ <https://www.macae.ufrj.br/nupem/>
     > http://lattes.cnpq.br/3629226944950076
    <http://lattes.cnpq.br/3629226944950076>
     >
    https://scholar.google.com.br/citations?user=p-PRvd4AAAAJ&hl=pt-BR
    <https://scholar.google.com.br/citations?user=p-PRvd4AAAAJ&hl=pt-BR>
     > https://www.researchgate.net/profile/Carlos_Barboza3
    <https://www.researchgate.net/profile/Carlos_Barboza3>
     >
     >? ? ? ? ? [[alternative HTML version deleted]]
     >
     > _______________________________________________
     > R-sig-mixed-models at r-project.org
    <mailto:R-sig-mixed-models at r-project.org> mailing list
     > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
    <https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models>

-- 
Universidade Federal do Rio de Janeiro (UFRJ)
Instituto de Biodiversidade e Sustentabilidade - NUPEM
Caixa Postal 119331, CEP 27910-970
Maca?, RJ, Brazil
https://www.macae.ufrj.br/nupem/ <https://www.macae.ufrj.br/nupem/>
http://lattes.cnpq.br/3629226944950076 
<http://lattes.cnpq.br/3629226944950076>
https://scholar.google.com.br/citations?user=p-PRvd4AAAAJ&hl=pt-BR 
<https://scholar.google.com.br/citations?user=p-PRvd4AAAAJ&hl=pt-BR>
https://www.researchgate.net/profile/Carlos_Barboza3 
<https://www.researchgate.net/profile/Carlos_Barboza3>

Comparing mixed models

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