st: specifying random effects in -xtmixed- for pretest/posttest clustered design

["Michael I. Lichter" <mlichter@buffalo.edu>]

I am having difficulties figuring out how to specify the random effects 
in -xtmixed- for my study design, and I haven't been able to find 
anything helpful in the archives or the manual.

My study is a standard cluster-randomized, two-condition, two-time-point 
trial with balanced allocation of clusters to conditions and only 
moderate variation in cluster size, with no stratification, crossing, 
matching, or anything else. Suppose I have one record per time point per 
person with variables:

c - study condition (control or intervention)
t - time point (pretest or post-test)
m - ID # for individual enrolled in trial
g - group #
y - study result

I am taking my guidance from David Murray's DESIGN AND ANALYSIS OF 
GROUP-RANDOMIZED TRIALS and trying to follow his example for what he 
calls an "unadjusted time x condition analysis" for "nested cohort 
designs" (pp. 296-311). The model, with subscripts omitted, looks like 
this: Y = mu + c + t + tc + G + M + TG + MT + e, where mu is the grand 
mean, tc is the interaction effect t*c (same for TG and MT), and G, M, 
TG, and MT are random effects.

Is any of these correct given the model?

xtmixed y cond t tc || G: || M: || TG: || MT: 
xtmixed y cond t tc || G: TG || M: MT 
xtmixed y cond t tc || G: M TG MT 

None of the above converge successfully with my data, but that doesn't 
mean they're all wrong ... Obviously, I'm unclear on how the 
specification of random effects works.

FWIW, Murray provides the following SAS code (with my variable names; 
and "ddf = 4,4,4" is for a specific example):

proc mixed info order=internal noclprint;
       class C G M T;
       model Y = C T C*T /ddf = 4,4,4 ddfm = res;
       repeated T /type = cs subject = M(G*C) r = 1 to 3 rcorr = 1 to 3;
       random G(C) TG(C);
       lsmeans C*T /slice=C slice=T c1 e;
       estimate `(I3 - I0)-(C3-C0)' C*T 1 -1 -1 1/cl e;
run;

I can run this in SAS, but the value of doing so is diminished by the 
fact that Murray's commands and annotations are about 10 years out of 
date; I'd rather do it in Stata if possible.

Thanks.

--
Michael I. Lichter, Ph.D.
Research Assistant Professor & NRSA Fellow
UB Department of Family Medicine / Primary Care Research Institute
UB Clinical Center, 462 Grider Street, Buffalo, NY 14215
Office: CC 125 / Phone: 716-898-4751 / E-Mail: mlichter@buffalo.edu

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