[R-sig-eco] nested mixed model?

[Andrew Kosydar]

Hi Mauro,

I agree with both Thierry and Luciano, considering your nested design the random effects lie at the level of the individual.  My only concern is that given the coding below, only the intercept varies and the slopes are set to be equal for the random variables.  From what I have read (e.g. Schielzeth and Forstmeier 2008, Behavioral Ecology), not investigating the slopes of the random variables can lead to spurious results.  I would also consider using Markov Chain Monte Carlo (MCMC) approximations (see Bolker et al. 2009, TREE).  However, I don't know if MCMC estimations work with nested designs.  Hence, perhaps the following might work?


tooth.lmer<-lmer(response ~ species, data=tooth, random=~age_of_individual|individual/bone/tooth)
tooth.pval<-pvals.fnc(tooth.lmer, nsim=1000, withMCMC=TRUE)
tooth.pval$fixed
tooth.pval$random


Perhaps others have an opinion regarding variation of slopes and intercepts with mixed effects models?  And the use of MCMC estimations with nested designs?

All the best,

Andrew



Andrew Kosydar
University of Washington
Department of Biology
24 Kincaid Hall, Box 351800
Seattle, WA 98195
USA




On Wed, 3 Feb 2010, ONKELINX, Thierry wrote:

> I aggree with Luciano. You should take the individual into account. The
> point is only relevant as a random effect if you have multiple records
> per point.
>
> I would use something like lme(response ~ species, data=tooth,
> random=~1|individual/bone/tooth)
>
> HTH,
>
> Thierry
>
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> say what the experiment died of.
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>
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> -----Oorspronkelijk bericht-----
> Van: r-sig-ecology-bounces at r-project.org
> [mailto:r-sig-ecology-bounces at r-project.org] Namens Luciano Selzer
> Verzonden: woensdag 3 februari 2010 13:59
> Aan: Mauricio Cifuentes
> CC: r-sig-ecology at r-project.org
> Onderwerp: Re: [R-sig-eco] nested mixed model?
>
> Hi, I'm by no means an expert, just an PhD student. But in my humble
> opinion shouldn't you consider the individual effect? I think that the
> microtexture could be influenced by this.
> Luciano
>
>
> 2010/2/3 Mauricio Cifuentes <mcifuent at gmail.com>
>
>> Hi everybody,
>>
>> I am trying to fit a model in R using the lme() function. I would like
>
>> to have your opinion about what I did and if there are better ways to
>> resolve this analysis. First Let me explain you how look the data that
>
>> we are analyzing. We want to compare the tooth microtexture of four
>> species of ungulates.
>>
>> For that we have taken pictures in eight different points within each
>> tooth of one individual. We used as many teeth as were available for
>> each individual taken in account their position and at the same time
>> separating them by the place they were located (mandible: down tooth;
>> maxilla: upper tooth).
>>
>> I am not an expert, but until here the model looks as nested design,
>> please let me know if I am wrong. In summary we have the following
>> hierarchy arrangement:
>>
>> Species (4 species) > bone(mandible or maxilla) > tooth > points
>> within each tooth (8 points).
>>
>> I have fitted this model using: lme(response ~ species, data=tooth,
>> random=~1|bone/tooth/points,na.action=na.omit)
>>
>> I will be really grateful if you can give me your opinion about that.
>>
>> Best wishes
>>
>> Mauro
>>
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