[R] understanding the verbose output in nlme

[Greg Distiller]

Hi
I have found some postings referring to the fact that one can try and 
understand why a particular model is failing to solve/converge from the 
verbose output one can generate when fitting a nonlinear mixed model. I am 
trying to understand this output and have not been able to find out much:

**Iteration 1
LME step: Loglik: -237.4517 , nlm iterations: 22
reStruct  parameters:
  subjectno1   subjectno2   subjectno3   subjectno4   subjectno5 
subjectno6
 -0.87239181   2.75772772  -0.72892919 -10.36636391   0.55290322 
0.09878685

PNLS step: RSS =  60.50164
 fixed effects:2.59129  0.00741764  0.57155
 iterations: 7

Convergence:
   fixed reStruct
5.740688 2.159285

I know that the Loglik must refer to the value of the log likelihood 
function, that the values after "fixed effects" are the parameter estimates, 
and that the bit after Convergence obviously has something to so with the 
convergence criteria for the fixed effects and the random effects structure. 
I did manage to find a posting where somebody said that the restruct 
parameter is the log of the relative precision of the random effects? The 
one thing that is a bit confusing to me is that it appears as if the fixed 
effects convergence must be zero (or close to it) as one would expect but in 
one of my converged models the output showed a restruct value of 0.72 ?



Then I have no idea what the numbers under subjectno1-6 are, especially as I 
have 103 subjects in the data!



Can anyone help shed some light on this output and how it can be used to 
diagnose issues with a model?



Many thanks



Greg