Random effects redux

Random effects redux

Post by William Dudle » Thu, 10 Sep 1998 04:00:00

Earlier today I thought I posted this note, but have not seen any response.
At the risk of being a pesk, I've reposted the message.


I am trying to run a one way anova with a single random effect.
The independent variable (Group) has three levels.
Nested within each Group are 4 to 5 sites with about 50 - 60 subjects in
each site.  Thus I have about 15 sites and an total N of about 1000

I am considering site as a random variable because we have randomly selected
(and assigned to conditions) these sites from a
larger sampling frame.

I am using the following syntax.

 wgt_tot   BY group site
  /RANDOM = site
  /EMMEANS = TABLES(group)
  /EMMEANS = TABLES(group*site)
  /DESIGN = group site group*site .

The output shows zero degrees of freedom for my "group" variable.  I wonder
if anyone has suggestions about what I am doing wrong.
(I have run the same syntax without the interaction and have the same problem).



William N Dudley, PhD
Asst Professor
Dept Behavi*Science and Health Education
Rollins School of Public Health
Emory University
Atlanta 30322
Phone 404 727 2447
FAX   404 727 1369


Random effects redux

Post by Michael Kruge » Thu, 10 Sep 1998 04:00:00

I'm not sure but from looking at your syntax it appears that you are asking for
fully crossed factorial design with site crossed with group, rather than nested
within group.


1. PROC MIXED: Random effect model with no residual variance

Is it possible to specify a random effect model without estimating a
residual variance?

With GPA measured on six regularly-spaced occasions, I want to treat
occasion as a random effect with an unstructured G matrix and a null R
matrix.  The log looks like this:

118  proc mixed covtest;
119  class occas;
120  model gpa=occas /noint solution;
121  random occas /subject=student type=un g gcorr;
122  run;

NOTE: Convergence criteria met.
NOTE: Estimated G matrix is not positive definite.

This makes sense because the estimated residual variance and one of
the elements of G are redundant. I would like to fix the residual
variance at zero.  Is this possible?  If so, how?

I realize that this model can be easily estimated using the REPEATED
subcommand with an unstructured R matrix and a null G matrix, but I
want to it the other way around.

Any help would be greatly appreciated.



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