Thanks for the reply...will give some thought to your suggestion about stepping through the function. I have read the Pinheiro and Bates book, in fact its my primary reference for getting into the nonlinear mixed models with R. Lastly wrt the bit under subjects 1-6, I had thought about it being an estimated random effect but in this model there are 2 random effects so not sure if that holds... thanks again...
----- Original Message ----- From: "Spencer Graves" <[EMAIL PROTECTED]> To: "Greg Distiller" <[EMAIL PROTECTED]> Cc: <[email protected]> Sent: Sunday, June 04, 2006 8:49 PM Subject: Re: [R] understanding the verbose output in nlme > I don't know, but if it were my question, I think I could find > out by making local copies of the functions involved and stepping > through the algorithm line by line using "debug" (see, e.g., > "http://finzi.psych.upenn.edu/R/Rhelp02a/archive/68215.html";). > > Have you read Pinheiro and Bates (2000) Mixed-Effects Models > in S and S-Plus? If no, I encourage you to do so. Over the past 4 > years or so, I've probably spent more time with this book and referred > more people to it than any other. Doug Bates is a leading original > contributor in this area, and I believe you will find this book well worth > your money and your time. > > Regarding "the numbers under subjectno1-6", I'm guessing that > these may be the current estimates of the random effects for the first 6 > of the 103 subjects. The purpose of "verbose" is NOT to dump everything > but only enough to help you evaluate whether the algorithm seems to be > converging. > > hope this helps. > Spencer Graves > > Greg Distiller wrote: >> 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 >> >> ______________________________________________ >> [email protected] mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide! >> http://www.R-project.org/posting-guide.html > > ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
