Thanks for your reply Robert,

 Could you be more specific about your proposed methods? I have not tested
any... Do you think you could tell me more about it and how I could perform
this in R?

 Thank you,

 Tommy



2013/7/3 Robert A LaBudde <ral@lcfltd.com>

> The obvious method would appear to be standard errors computed from
> bootstrap or crossvalidation samples.
>
> What's the issue with this?
>
> At 04:33 AM 7/3/2013, tommy gaillard wrote:
>
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>>
>> Thanks for your reply David.
>> In my area, animal behavior ecology,  the comparison of random slope
>> between studies is very advantageous. It has been underestimate so far but
>> many authors have pointed out its importance. This is why LRT has limits
>> because it only tells you whether a random effect is statistical
>> significant or not. It might be enough in your area but in my field I need
>> to give a biological meaning of my statistical results.
>>   There are a couple of alternative to LRT:
>> 1) Iterative approach: based on the AIC score
>> 2) Pseudo-bayesian approach: mcmcsamp
>> 3) Bayesian approach: based on DIC score
>>
>>  I am more familiar with the AIC approach and was tempted to use this one.
>> I know there are some drawbacks though, this is why I would like to
>> discuss
>> with you those different methods and to choose the more appropriate one to
>> give a biological meaning of my results.
>>
>>  Thanks,
>>
>>  Tommy
>>
>>
>>
>>
>>
>>
>>
>>
>> 2013/7/3 David Duffy <David.Duffy@qimr.edu.au>
>>
>> > On Tue, 2 Jul 2013, tommy gaillard wrote:
>> >
>> >  I am aiming to assess the inter-individual variability of both random
>> >> intercept and slope in response to multiple changing variables.
>> >> In order to so, several studies have compared models two by two by
>> >> changing
>> >> their structure. For example, to know whether there is a difference in
>> the
>> >> plasticity of the responses between individuals, they compare a model
>> with
>> >> both the interest variable*Identity individual as random effect and a
>> >> model
>> >> with only "Identity individual" ad random effect. They then realize a
>> >> loglikelihood test and base their results only on the pvalues.
>> >>
>> >> I am looking for an alternative as I have been strongly recommended to
>> >> base my results on effect size (and 95% IC) rather than on pvalues.
>> This
>> >> has indeed several advantages as it gives the biological magnitude of
>> an
>> >> effect, its uncertainty and it is comparable between studies.
>> >>
>> >
>> > Hopefully someone else will chime in, but I don't know if I would
>> consider
>> > an estimate of random slope effect as necessarily comparable between
>> > *studies* - that will be really depend on the area.  If the dataset is
>> not
>> > too large, I'd probably find a graphical presentation of the fitted
>> > regression line for each individual more biologically meaningful. Also,
>> a
>> > plot of the distribution of the individual slopes ("raw", or predicted
>> from
>> > your mixed model), as this may not be a single Gaussian.
>> >
>> > My simple minded way of thinking is "can we summarize these data using a
>> > model without interactions?", do a LRT and try and work out its
>> > distribution under the null (a hard problem!), and if interaction is
>> > nonignorable, then present what's going on as complicated.
>> >
>> > Just 2c.
>> >
>> > | David Duffy (MBBS PhD)                                         ,-_|\
>> > | email: davidD@qimr.edu.au  ph: INT+61+7+3362-0217 fax: -0101  /     *
>> > | Epidemiology Unit, Queensland Institute of Medical Research   \_,-._/
>> > | 300 Herston Rd, Brisbane, Queensland 4029, Australia  GPG 4D0B994A v
>> >
>>
>>
>>
>> --
>> *Tommy Gaillard
>> Etudiant stagiaire CNRS*
>>
>> Université de Dijon
>> Master 2 Recherche
>> Tel: 06-71-81-94-66
>> Email: tommy.gaillard40@gmail.com
>>
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>>
>>
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>>
>
> ==============================**==============================**====
> Robert A. LaBudde, PhD, PAS, Dpl. ACAFS  e-mail: ral@lcfltd.com
> Least Cost Formulations, Ltd.            URL: http://lcfltd.com/
> 824 Timberlake Drive                     Tel: 757-467-0954
> Virginia Beach, VA 23464-3239            Fax: 757-467-2947
>
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> ==============================**==============================**====
>
>


-- 
*Tommy Gaillard
Etudiant stagiaire CNRS*
Université de Dijon
Master 2 Recherche
Tel: 06-71-81-94-66
Email: tommy.gaillard40@gmail.com

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