On 12 May 2008, at 09:29, Dieter Menne wrote:
Federico:
First, mixed models are different from "standard 101 Anova", and
quite a lot
of the nesting stuff I used to ponder about 30 year ago when I started
teaching this is no longer relevant and works implicitely when you
code the
parameters correctly.
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. >>
Good to know that you are sure what is "right"; probably == SAS.
Since most
people active in the lme-business have read
http://wiki.r-project.org/rwiki/doku.php?id=guides:lmer-tests
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/76742.html
carefully, you might be rather lonely.
I will. While I do, feel free to have a look at Appendix A.3 (page
App6, at the end of the book) of the Zar 'Biostatistical Analysis',
IV ed, second table from the top. That's where I get the feeling for
what's right or wrong. I surely cannot get it from SAS because I
never had it. I never had the budget for it, so much so I had to lear
how to use R from the start because it was free and that was the
budget of my department had for stats software
All in all, if you feel statistical analysis has moved forth from
such humble beginnings (the book I mean, not SAS), and you can
convince of that every ref for every paper you submit, please do tell
me how you do it, it would be more valuable than knowing how to fit
my model.
Cheers,
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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