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...use. Unfortunately, I didn't find out how to use covariance structures (e. g. corSymm(), corAR1()). Is there a way to use them similarly as in lme ? Is it implemented ? If somebody knows, please let me know. Thank you very much in advance, Stephan ----------------------------- Dr. Stephan Moratti (PhD) Dept. of Psychology University of Konstanz P.O Box D25 Phone: +40 (0)7531 882385 Fax: +49 (0)7531 884601 D-78457 Konstanz, Germany e-mail: Stephan.Moratti at uni-konstanz.de http://www.clinical-psychology.uni-konstanz.de/

...&(row-1)* : missing value where TRUE/FALSE needed This error only occured in compination with "layout". It was no problem to plot all subjects on one page. Further, this error did not occur using older version of R (1.8 or 1.7). Did somebody encounter similar problems ? Stephan Moratti -- Dipl. Psych. Stephan Moratti Dept. of Psychology University of Konstanz P.O. Box D25 D-78457 Konstanz, Germany Tel.: +49 (0) 7531 882385

...n(2*pi*Time))) fm5Ovary.lme<-update(fm1Ovary.lme,corr=corARMA(p=1,q=1)) I get follwing error message: Error in "coef<-.corARMA"(`*tmp*`, value = c(62.3428455941166, 62.3428517930051 : Coefficient matrix not invertible Does somebody know why it doesn't work ? Stephan Moratti ----------------------------- Dipl. Psych. Stephan Moratti Dept. of Psychology University of Konstanz P.O Box D25 Phone: +40 (0)7531 882385 Fax: +49 (0)7531 884601 D-78457 Konstanz, Germany e-mail: Stephan.Moratti at uni-konstanz.de http://www.clinical-psychology.uni-konstanz.de/

Hi I constructed a mixed-effects model from longitudinal repeated measurements of lab values in 22 patients seperated into two groups with the groups as fixed effect using lme. I thought about using the jackknife procedure, i. e., removing any one subject and calculating the fixed effect, to assess the stability of the fixed effect and thereby validate the model. I suppose this has been done in

Dear all, I have a performance problem in terms of computing time. I estimate mixed models on a fairly large number of subgroups (10000) using lme(.) within the by(.) function and it takes hours to do the calculation on a fast notebook under Windows. I suspect by(.) to be a poor implementation for doing individual analysis on subgroups. Is there an alternative and more efficient way for doing

...f in foreign function call (arg 1)" If I skip observation subject 15 (row 15 above) the computation is successfull. Is it because of the similar values ? Does it fail to estimate a general variance structure ? Is there a better way than skipping row 15 ? Thanks for some suggestions, Stephan Moratti ----------------------------- Dipl. Psych. Stephan Moratti Dept. of Psychology University of Konstanz P.O Box D25 Phone: +40 (0)7531 882385 Fax: +49 (0)7531 884601 D-78457 Konstanz, Germany e-mail: Stephan.Moratti at uni-konstanz.de http://www.clinical-psychology.uni-konstanz.de/

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