On 8/18/05, Christoph Lehmann <[EMAIL PROTECTED]> wrote: > Hi, > We have data of two groups of subjects: 32 elderly, 14 young adults. for > each subject we have 15 observations, each observation consisting of a > reaction-time measure (RT) and an activation maesure (betadlpcv). > since we want to analyze the influence of (age-)group and RT on the > activation, we call: > > lme(betadlpcv ~ RT*group, data=our.data, random=~ RT |subject) > > this yields: > Error in MEEM(object, conLin, control$niterEM) : > Singularity in backsolve at level 0, block 1 > In addition: Warning message: > Fewer observations than random effects in all level 1 groups in: > lme.formula(betadlpcv ~ RT * group, data = patrizia.data, random = ~RT | > > what's the problem here?
It seems that you only have one observation per subject and you are trying to estimate a model with two random effects per subject plus the per-observation noise term. These terms are completely confounded. > > thanks for your kind help > christoph > > -- > Lust, ein paar Euro nebenbei zu verdienen? Ohne Kosten, ohne Risiko! > Satte Provisionen für GMX Partner: http://www.gmx.net/de/go/partner > > > > ______________________________________________ > [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
