# [R] SAS Proc Mixed and lme

From: Kellie J. Archer, Ph.D. <kjarcher_at_vcu.edu>
Date: Sat 01 Jul 2006 - 05:08:53 EST

I am trying to use lme to fit a mixed effects model to get the same results as when using the following SAS code:

proc mixed;
class refseqid probeid probeno end;
model expression=end logpgc / ddfm=satterth; random probeno probeid / subject=refseqid type=cs; lsmeans end / diff cl; run;

There are 3 genes (refseqid) which is the large grouping factor, with 2 probeids nested within each refseqid, and 16 probenos nested within each of the probeids.

I have specified in the SAS Proc Mixed procedure that the variance-covariance structure is to be compound symmetric. Therefore, the variance-covariance matrix is a block diagonal matrix of the form,

V_1 0 0
0 V_2 0
0 0 V3

where each V_i represents a RefSeqID. Moreover, for each V_i the structure within the block is

v_{11} v{12}
v_{21} v{22}

where v_{11} and v_{22} are different probeids nested within the refseqid, and so are correlated. The structure of both v_{11} and v_{22} are compound symmetric, and v_{12} and v{21} contain a constant for all elements of the matrix.

I have tried to reproduce this using lme, but it is unclear from the documentation (and Pinheiro & Bates text) how the pdBlocked and compound symmetric structure can be combined.

fit.lme<-lme(expression~End+logpgc,random=list(RefSeqID=pdBlocked(list (~1,~ProbeID-1),pdClass="pdSymm")),data=dataset,correlation=corCompSym m(form=~1|RefSeqID/ProbeID/ProbeNo))

The point estimates are essentially the same comparing R and SAS for the fixed effects, but the 95% confidence intervals are much shorter using lme(). In order to find the difference in the algorithms used by SAS and R I tried to extract the variance-covariance matrix to look at its structure. I used the getVarCov() command, but it tells me that this function is not available for nested structures. Is there another way to extract the variance-covariance structure for nested models? Does anyone know how I could get the var-cov structure above using lme?

Kellie J. Archer, Ph.D.
Assistant Professor, Department of Biostatistics Fellow, Center for the Study of Biological Complexity Virginia Commonwealth University
1101 East Marshall St., B1-066
Richmond, VA 23298-0032
phone: (804) 827-2039
fax: (804) 828-8900
e-mail: kjarcher@vcu.edu
website: www.people.vcu.edu/~kjarcher

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