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$niterEM) :
Singularity in backsolve at level 0, block 1
In addition: Warning message:
Fewer observations than random effects in all level 1 groups in:
lme.formula(betadlpcv ~ RT * group, data = patrizia.data, random = ~RT |
what's the problem here?
thanks for your kind help
christoph
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On 8/18/05, Christoph Lehmann <christoph.lehmann at gmx.ch> wrote:> Hi, > We have data of two groups of subjects: 32 elderly, 14 young adults. for > each subject we have 15 observations, each observation consisting of a > reaction-time measure (RT) and an activation maesure (betadlpcv). > since we want to analyze the influence of (age-)group and RT on the > activation, we call: > > lme(betadlpcv ~ RT*group, data=our.data, random=~ RT |subject) > > this yields: > Error in MEEM(object, conLin, control$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 f??r GMX Partner: http://www.gmx.net/de/go/partner > > > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html > >
Christoph Lehmann <christoph.lehmann <at> gmx.ch> writes:> > 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$niterEM) : > Singularity in backsolve at level 0, block 1If you really have 15 observations (690 lines) it should be enough to estimate the model (see below). Assume you had some degenerate case. From a psychophysical point of view, I am surprised that reaction time is on the right side, but that's off-subject. Dieter ---- sub = data.frame(subject=1:46,group=c(rep("old",32),rep("young",14))) sub$slope = 2.5+as.numeric(sub$group)+rnorm(46,0.5) beta = data.frame( subject=rep(sub$subject,15), group=rep(sub$group,15), slope=rep(sub$slope,15), RT=rnorm(46*15,100,20)) beta$betadlpcv = beta$slope*beta$RT + rnorm(46*15,0.1) library(nlme) beta.lme = lme(betadlpcv ~ RT*group, data=beta, random=~ RT |subject) summary(beta.lme)