mixed model fitting between R and SAS

Please don't cross-post.

- corAR1() models the correlation between the residuals of the two time points. 
- if you want a specific correlation structure for biopsy locations the you must use on of the pdClasses() and use biopsy location as random slope of pid rather than random effect nested in pid.

#basic structure = positive definitive symmetrical variance/covariance matrix
lme(y~age + time * trt, random=~0  + biopsy.site|pid, data = test,  correlation=corAR1(~time))
#no correlation between biopsy location and different variance
lme(y~age + time * trt, random=list(pid  = pdDiag(~0  + biopsy.site), data = test,  correlation=corAR1(~time))
#no correlation between biopsy location and equal variance
lme(y~age + time * trt, random=list(pid  = pdIdent(~0  + biopsy.site), data = test,  correlation=corAR1(~time))

Note that since you have only two biopsy locations there will be no difference between pdSymm (the default) and pdCompSymm

Best regards,

Thierry
----------------------------------------------------------------------------
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek
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Research Institute for Nature and Forest
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tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be
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-----Oorspronkelijk bericht-----
Van: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
Namens array chip
Verzonden: maandag 8 augustus 2011 8:48
Aan: r-sig-mixed-models at r-project.org
CC: r-help
Onderwerp: [R] mixed model fitting between R and SAS

Hi al,

I have a dataset (see attached), which basically involves 4 treatments for a
chemotherapy drug. Samples were taken from 2 biopsy locations, and biopsy
were taken at 2 time points. So each subject has 4 data points (from 2 biopsy
locations and 2 time points). The objective is to study treatment difference.

I used lme to fit a mixed model that uses "biopsy.site nested within pid" as a
random term, and used corAR1() as the correlation structure for between the 2
time points:


library(nlme)

test<-read.table("test.txt",sep='\t',header=T,row.names=1)
fit<-lme(y~age + time * trt, random=~1|pid/biopsy.site, data = test,
correlation=corAR1())

First, by above model specification, corAR1() is used for the correlation between
the 2 time points; what is the correlation structure implicitly used for between
biopsy locations? How do I specify a particular correlation structure for between
biopsy locations in this situation?

Second, does anyone know how to write the above mixed model in SAS? One of
my colleagues wrote the following, but it gave me different results:

proc mixed data=test;

class time trt pid biopsysite;
model y=age time trt time*trt;
random biopsysite
repeated pid / type=ar(1)
run;

Is there anyone familiar with SAS and know if the above SAS code does what the
R code does?

Many thanks

John