For those interested, I've provided steps to running a multivariate analysis in the MIXED procedure in PASW 17.
In order to run a multivariate analysis employing the MIXED procedure, one would need to add an indicator variable as a link to the response variables to the data set. Also, in order to allow for separate intercepts for each response variable, the grand intercept must be excluded, and to allow for separate slopes, the fixed effects covariates should be added only by interacting them with the indicator variable. Note that the response is assumed to be a multivariate normal.
Here is an example:
---------------------------
ID Indic Y X1
1 1 150 22
1 2 70 33
2 1 180 24
2 2 72 48
3 1 163 2
3 2 62 23
.
.
.
N
---------------------------
where
ID = identification number, repeating for each unit
Indic = indicator of the dependent variables (i.e. 1=height, 2=weight)
Y = value on that specific dependent variable (i.e. in inches for height, in pounds for weight)
X1 = fixed effects covariate
---------------------------
The code to run such a model would be as follows:
MIXED Y BY Indic WITH X1
/FIXED=Indic Indic*X1 | NOINT SSTYPE(3)
/METHOD=REML
/PRINT=DESCRIPTIVES SOLUTION
/RANDOM=INTERCEPT | SUBJECT(ID) COVTYPE(VC).
----------------------------
Here are a couple of articles that explain running a multivariate analysis in linear mixed modeling:
http://www2.sas.com/proceedings/sugi23/Stats/p229.pdfhttp://arxiv.org/ftp/arxiv/papers/0705/0705.0568.pdf
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***Here's a more eloquent explanation in the SAS google group that I read earlier on when learning the how to run such an analysis in SAS:
http://listserv.uga.edu/cgi-bin/wa?A2=ind0402D&L=sas-l&P=R20058----------------------------
I welcome thoughts on this topic.
Best,
Ryan