Post on the r-sig-mixed-models list, not here.*

-- Bert
 * Or consult a local statistician, as your problem appears to be
insufficient statistical knowledge, rather than R-related. In particular,
fitting a (mixed effect) linear model without an intercept is almost always
unwise.

On Thu, Jul 12, 2012 at 12:37 AM, Julien Leblud
<julien.leblud@umons.ac.be>wrote:

> Dear list,
>
> I'm quite confused when interpreting results from a mixed linear model.
>
> For example, working on Iris data frame, I want to know the effect of
> species on slope of the model  "Petal.Length~Sepal.Length"
>
> I write this :
>
> data(iris)
> reg01 <- lm(Petal.Length~Sepal.Length + Sepal.Length:Species, data=iris)
> summary(reg01)
>
> It gives me a summary table with lm for the first factor, i.e setosa, and
> the effects of each levels of Species on interactions, which mean on the
> slope.
>
> Now, i would like a model with intercept =0. I should write this:
>
> data(iris)
> reg02 <- lm(Petal.Length~Sepal.Length + Sepal.Length:Species - 1 ,
> data=iris)
> summary(reg02)
>
> ...But results is meaningless for me...
>
> Any idea to fit a model like this?
> Thanks a lot !
>
> Julien
>
> --
> ***********************************************
> Julien Leblud
>
> Numerical Ecology of Aquatic Systems
> Mons University, Belgium
>
> http://econum.umons.ac.be/**labo/ <http://econum.umons.ac.be/labo/>
>
> ..............................**<°}))><........
>
> Ecologie Numérique des Milieux Aquatiques
> Université de Mons
>
> tel. +32 (0) 65 37 36 65
>
> Pentagone (aile 3D)
> 6, Avenue du Champ de Mars
> 7000 Mons, Belgium
>
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>



-- 

Bert Gunter
Genentech Nonclinical Biostatistics

Internal Contact Info:
Phone: 467-7374
Website:
http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm

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