Summary: proc mixed vs. lme

Thu, Oct 10, 2002 12:40 AM

Hi Freq

if you like to get familiar with logistic regression in R, I would
recommend the text book of Venables and Ripley (Modern Applied 
Statistics with S-PLUS). All data sets and functions 
are available for R in the MASS-library. The MASS-library could be down
loaded 
from http://cran.r-project.org/bin/windows/contrib/VR.zip (e.g.. Windows
users).
The glm function plays the key role. With the help of this function you
could fit
logistic regression models. First step in the material could be:

library(MASS)
?glm

Regards,

Dominik

-----Original Message-----
From: Feng Zhang [mailto:f0z6305 at labs.tamu.edu]
Sent: mercredi, 9. octobre 2002 22:26
To: Grathwohl,Dominik,LAUSANNE,NRC/NT; r-help at stat.math.ethz.ch
Subject: Re: [R] Summary: proc mixed vs. lme


Sorry to bother you.
I want to know if there are some Logistical Regression
functions in R?

Thanks.



----- Original Message -----
From: "Grathwohl,Dominik,LAUSANNE,NRC/NT"
<dominik.grathwohl at rdls.nestle.com>
To: <r-help at stat.math.ethz.ch>
Sent: Wednesday, October 09, 2002 1:19 PM
Subject: [R] Summary: proc mixed vs. lme

Summary: proc mixed vs. lme

The objective of this summary is to help people
to get more familiar with the specification of
random effects with proc mixed or lme.
Very useful are the examples of Ramon Littell's book:
"SAS System for Mixed Models (1996)"
(http://ftp.sas.com/samples/A55235)
The same data set's are kindly made available
by Douglas Bates in the library(SASmixed).
In the help file are examples of the lme statements
equivalent to the proc mixed ones.

To explain the different estimates,
Hein and Brian suppose to check whether both
analyses with SAS and R uses ML estimates
or REML estimates. However, this was not the problem,
the default in proc mixed and lme is already REML.
Douglas advise me to use his option:
options( contrasts = c(unordered = "contr.SAS",
ordered = contr.poly"))
However, I already used this option,
because I copied the code from the SASmixed help file.
Peter gave me the first hint
and this solves the problem:
To change the model formula in lme,
from: strength ~ Program * Time
to: strength ~ factor(Program) * factor(Time)
Now the option statement grasp!
For people like me who try to get familiar
with the specification of random effects
would it helpful if the help file of SASmixed
would be updated or the variables time and program
would be already introduced as factors
in the Weights data set.

Thank you all for the useful advises,

Dominik

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