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

[Jeph Herrin <junk@spandrel.net>]

Try,

 xtmixed y cond t tc || g: cond t tc

this tells -xtmixed- to estimate random effects across group
for cond, t, and tc.

I don't know what murray means by including M as a random
effect (and don't feel like pulling his book off the shelf
to check), but I'm pretty sure you don't want that unless
you have multiple records per person per time point.

hth,
Jeph



Michael I. Lichter wrote:
> 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.
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