proc GLM with R
At 05:15 18/12/2006, Cressoni, Massimo \(NIH/NHLBI\) [F] wrote:
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
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)
Thank you Massimo Cressoni run;
Michael Dewey http://www.aghmed.fsnet.co.uk