[R-sig-ME] [R] lme nesting/interaction advice

Federico Calboli f.calboli at imperial.ac.uk
Mon May 12 11:50:03 CEST 2008


On 12 May 2008, at 01:05, Andrew Robinson wrote:

> On Mon, May 12, 2008 at 10:34:40AM +1200, Rolf Turner wrote:
>>
>> On 12/05/2008, at 9:45 AM, Andrew Robinson wrote:
>>
>>> On Sun, May 11, 2008 at 07:52:50PM +0100, Federico Calboli wrote:
>>>>
>>>> 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].
>>>
>>> That may be so, but I've never needed to use one.
>>
>> 	So what?  This is still a standard, common, garden-variety
>> 	model that you will encounter in exercises in many (if not
>> 	all!) textbooks on experimental design and anova.
>
> To reply in similar vein, so what?  Why should R-core or the R
> community feel it necessary to reproduce every textbook example?  How
> many times have *you* used such a model in real statistical work,
> Rolf?

There is a very important reason why R (or any other stats package)  
should *easily* face the challenge of bog standard models: because it  
is a *tool* for an end (i.e. the analysis of data to figure out what  
the heck they tell us) rather than a end in itself.

Bog standard models are *likely* to be used over and over again  
because they are *bog standard*, and they became such by being used  
*lots*.

If someone with a relatively easy model cannot use R for his job s/he  
will use something else, and the R community will *not* increase in  
numbers. Since R is a *community driven project*, you do the math on  
what that would mean in the long run.

Regards,

Federico

--
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




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