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$niterEM) : > Singularity in backsolve at level 0, block 1
If you really have 15 observations (690 lines) it should be enough to estimate the model (see below). Assume you had some degenerate case. From a psychophysical point of view, I am surprised that reaction time is on the right side, but that's off-subject. Dieter ---- sub = data.frame(subject=1:46,group=c(rep("old",32),rep("young",14))) sub$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) ______________________________________________ R-help@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