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proc GLM with R

2 messages · Cressoni, Massimo (NIH/NHLBI) [F], Michael Dewey

#
I want to migrate from SAS to R.
I used proc mixed to do comparison between multiple groups and to perform
multiple comparison between groups since, as far as I know, proc mixed does not make assumptions about the data and so 
it is better than a simple anova (data must only be normal).
Es. how can I translate a code like this (two way anova with a factor of 
repetition) :


proc mixed;
class kind  PEEP codice;
model PaO2_FiO2 = kind PEEP kind*PEEP;
repeated /type = un sub=codice;
lsmeans kind*PEEP /adjust=bon;
run;

codice is a unique identifier of patient
kind is a variable which subdivided the patient (i.e. red or brown hairs)
PEEP is positive end expiratory pressure. These are the steps of a clinical
trial. Patient did the trial at PEEP = 5 and PEEP = 10

Thank you

Massimo Cressoni

run;
1 day later
#
At 05:15 18/12/2006, Cressoni, Massimo \(NIH/NHLBI\) [F] wrote:
You could investigate either nlme or lme4
The best documentation for nlme (which should be included in your system) is
@BOOK{pinheiro00,
   author = {Pinheiro, J C and Bates, D M},
   year = 2000,
   title = {Mixed-effects models in {S} and {S-PLUS}},
   publisher = {Springer-Verlag},
   address = {New York},
   keywords = {glm; mixed models}
}
lme4 is a more recent development by Bates which as yet has slightly 
fewer helper functions and no book.

Since you are assuming normal error you can use nlme. I am afraid I 
do not read SAS so I think it would be wrong of me to try to 
translate your example (traddutore, traditore and all that)
Michael Dewey
http://www.aghmed.fsnet.co.uk