Hi,
 
I am trying to run a multilevel model with time nested in people and
people nested in dyads (3 levels of nesting) by initially running a
series of models to test whether the slope/intercept should be fixed or
random.  The problem that I am experiencing appears to arise between the
random intercept, fixed slope equation AND.
 
(syntax:
rint<-lme(BDIAFTER~BDI+WEEK+CORUMTO, random=~1|DYADID/PARTICIP,
data=new) 
summary(rint))
 
the random slope, random intercept model 
 
(syntax: 
rslint<-lme(BDIAFTER~BDI+WEEK+CORUMTO, random=~CORUMTO|DYADID/PARTICIP,
data=new) 
summary(rslint))
 
at which point I obtain the exact same results for each model suggesting
that one of the model is not properly specifying the slope or intercept.
 
Or, I receive the following error message when I try to run the random
slope/random intercept model.
 
Error in solve.default(pdMatrix(a, fact = TRUE)) : 
        system is computationally singular: reciprocal condition number
= 6.77073e-017
 
(whether I receive an error message or the same results depends on the
specific variables in the model).
 
It has been suggested that I may need to change the default starting
values in the model because I may be approaching a boundary-is this a
plausible explanation for my difficulties?  If so, how do I do this in R
and can you refer me to a source that might highlight what would be
reasonable starting values?
If this does not seem like the problem, any idea what the problem may be
and how I might fix it?
 
Thank you so much for your assistance,
Christine Calmes
 
 
Christine A. Calmes, MA
Dept of Psychology
University at Buffalo: The State University of New York
Park Hall 216
Buffalo, NY 14260
ccalmes@buffalo.edu
(716) 645-3650 x578
 

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