lme nesting/interaction advice

On 10 May 2008, at 07:36, Kingsford Jones wrote:

Federico,

I think you'll be more likely to receive the type of response you're
looking for if you formulate your question more clearly.  The
inclusion of "commented, minimal, self-contained, reproducible code"
(as is requested at the bottom of every email sent by r-help) is an
effective way to clarify the issues.  Also, when asking a question
about fitting a model it's helpful to describe the specific research
questions you want the model to answer.

<snip>

I apprecciate that my description of the *full* model is not 100%  
clear, but my main beef was another.

The main point of my question is, having a 3 way anova (or ancova,  
if you prefer), with *no* nesting, 2 fixed effects and 1 random  
effect, why is it so boneheaded difficult to specify a bog standard  
fully crossed model? I'm not talking about some rarified esoteric  
model here, we're talking about stuff tought in a first year Biology  
Stats course here[1].

Now, to avoid any chances of being misunderstood in my use of the  
words 'fully crossed model', what I mean is a simple

y ~ effect1 * effect2 * effect3

with effect3 being random (all all the jazz that comes from this  
fact). I fully apprecciate that the only reasonable F-tests would be  
for effect1, effect2 and effect1:effect2, but there is no way I can  
use lme to specify such simple thing without getting the *wrong*  
denDF. I need light on this topic and I'd say it's a general enough  
question not to need much more handholding than this.

Having said that, I did look at the mixed-effects mailing list  
before posting here, and it looks like it was *not* the right place  
to post anyway:

'This mailing list is primarily for useRs and programmeRs interested  
in *development* and beta-testing of the lme4 package.'

although the R-Me is now CC'd in this.

I fully apprecciate that R is developed for love, not money, and if  
I knew how to write an user friendly frontend for nlme and lme4 (and  
I knew how to actually get the model I want) I'd be pretty happy to  
do so and submit it as a library. In any case, I feel my complaint  
is pefectly valid, because specifying such basic model should  
ideally not such a chore, and I think the powers that be might  
actually find some use from user feedback.

Once I have sorted how to specify such trivial model I'll face the  
horror of the nesting, in any case I attach a toy dataset I created  
especially to test how to specify the correct model (silly me).

Best,

Federico Calboli

[1] So much bog standard that the Zar, IV ed, gives a nice table of  
how to compute the F-tests correctly, taking into account that one  
of the 3  effects is randon (I'll send the exact page and table  
number tomorrow, I don't have the book at home).

<testdat.txt>
--
Federico C. F. Calboli
Department of Epidemiology and Public Health
Imperial College, St. Mary's Campus
Norfolk Place, London W2 1PG

Tel +44 (0)20 75941602   Fax +44 (0)20 75943193

f.calboli [.a.t] imperial.ac.uk
f.calboli [.a.t] gmail.com