[R-sig-ME] "slice(SAS)" with R

[fernando barbero]

Hi Thierry and all,
Well, Mr Paul Thompson has just posted what the slice command does so I
thank him very much, in
my personal case I am interested in the following:
1- I would like to seek differences in each population for each type of wing
(I have two types of wings and eight different populations)
2- and see if there are differences between the eight  different populations
(compare the populations between them). If I had been working with a
continuous response variable and a LME,  and no interaction between fixed
effects, I would have carried out a test with the glht function of Multcomp
package, but as I have a binary response variable (thus a GLM) and a
positive interaction between two fixed effects (population and type of wing)
I don t know how to go on
Best regards
Fernando
 
As I have said I am not a speacilist with SASThe slice command in SAS allows
to study 

-----Mensaje original-----
De: ONKELINX, Thierry [mailto:Thierry.ONKELINX at inbo.be] 
Enviado el: lunes, 12 de septiembre de 2011 05:08 a.m.
Para: fernando barbero; r-sig-mixed-models at r-project.org
Asunto: RE: [R-sig-ME] "slice(SAS)" with R

Dear Fernando,

You will have to tell us what the slice command does. Otherwise it will be
hard to give you advice.

Best regards,

Thierry

> -----Oorspronkelijk bericht-----
> Van: r-sig-mixed-models-bounces at r-project.org [mailto:r-sig-mixed-models-
> bounces at r-project.org] Namens fernando barbero
> Verzonden: vrijdag 9 september 2011 16:47
> Aan: r-sig-mixed-models at r-project.org
> Onderwerp: [R-sig-ME] "slice(SAS)" with R
> 
> Hello all, I have been working with data from 8 different tree populations
of an
> american beech, currently I have been recording the filling of seeds
(binary
> response variable)and have fitted a GLMM with lme4 which has this
> structure:
> 
> 
> 
> model<-lmer(
>
seedfilling~population+(1|population:tree)+typewing+typewing*population,fam
> i
> ly=binomial,data1)
> 
> 
> 
> where:
> 
> seedfilling is the binary response variable (1= filled seed,0=empty seed)
> 
> population is a fixed effect of population, I have eight different
populations
> 
> tree is a random effect nested under population (I harvested 15 trees
randomly
> chosen in every population)
> 
> typewing is the type of wing, as seeds in this tree species can have 2 or
3 wings
> 
> typewing * population is an interaction effect
> 
> I recorded the filling of 150 seeds in every tree
> 
> 
> 
> So far so cool. I have tested the significance of all effects with LRTs
and they all
> showed to be significant, now I want to study if there are any differences
> between populations (If I had a linear mixed model I would be using the
glht
> function of Multcomp package). Colleagues that work with SAS have told me,
> and in fact they have carried out,  this analysis using the "slice"
command but as
> I work with R I want to do it with it, do you know if this can be carried
out?
> 
> Best regards
> 
> Fernando
> 
> 
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> 
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