[R] Summary: proc mixed vs. lme

[Feng Zhang]

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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