[R-sig-ME] random effects specification

[Sebastian P. Luque]

Dear lmers,

Indeed this has been a very helpful thread.  Thanks to all for your
feedback/time!

All the best,
Sebastian



On Mon, 05 May 2008 10:12:59 +0800,
Julie Marsh <marshj02 at student.uwa.edu.au> wrote:

> Dear Sebastian, Sounds as if you have received great advice already.
> Just a short note - I believe you are missing the fixed-effect
> intercept in your model which I have denoted as simply "B" in your
> notation below.  This is often denoted as Beta0 or B0 in textbooks
> (sorry no subscripts or greek letters printing in this email!).

> y_{ijk} = B + B_j + B_k + B_{jk} + b_i + e_{ijk} i=1,...,20; j=A,B;
> k=a,b,c

> kindest regards, julie.




> Quoting "Sebastian P. Luque"
> <spluque at gmail.com>:

>> Hi again,

>> I've made further explorations into lmer, toying with the example I
>> showed earlier:


>> ---<---------------cut here---------------start-------------->---
>> set.seed(1000) rCom <- rnorm(2, mean=5, sd=0.5) rTr <- rep(rCom /
>> 1.1, 2) nbase <- rnorm(60, 10, 0.1)

>> ## 20 individuals; 10 in community "A" and 10 in "B", each receiving
>> 3 ## different treatments once.  dta <-
>> within(expand.grid(community=LETTERS[1:2], treatment=letters[1:3],
>> id=1:10), { id[community == "B"] <- id[community == "B"] + 10 id <-
>> as.factor(id) n <- rCom[as.numeric(community)] +
>> rTr[as.numeric(treatment)] + nbase }) dta <- dta[order(dta$id,
>> dta$community, dta$treatment), ]

>> ## Simulate an interaction dta$n[dta$community == "A"] <-
>> rev(dta$n[dta$community == "A"]) ## Have a look xyplot(n ~ treatment
>> | community, data=dta, groups=id, type="b", pch=19, cex=0.3)

>> ## We test for community (A, B) and treatment (a, b, c) fixed
>> effects, ## their interactions, and use random effects for subject
>> (1:20).  Am I ## writing this correctly?  ## ## y_{ijk} = B_j + B_k +
>> B_{jk} + b_i + e_{ijk} i=1,...,20; j=A,B; k=a,b,c n.lmer1 <- lmer(n ~
>> community * treatment + (1 | id), dta) ---<---------------cut
>> here---------------end---------------->---


>> I'm a bit confused whether I'm describing the model being fit
>> correctly (not the lmer call, but the model description in the
>> comment above), and how it could be described in matrix form.  I
>> think this type of exercises would help me grasp the syntax
>> conventions better.

>> Another issue is that the lmer call results in a warning:

>> ---<---------------cut here---------------start-------------->---
>> Warning message: In .local(x, ..., value) : Estimated variance for
>> factor ?id? is effectively zero ---<---------------cut
>> here---------------end---------------->---


>> which I presume is due to the fact that the data are unreplicated,
>> i.e. individuals get each treatment only once.  Are there any gotchas
>> in the interpretation of the results after this warning?

>> Thanks once again!

>> -- Seb

>> _______________________________________________
>> R-sig-mixed-models at r-project.org mailing
>> list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models




Cheers,

-- 
Seb