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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