On Tue, Oct 26, 2010 at 12:27 PM, Dimitri Liakhovitski <dimitri.liakhovit...@gmail.com> wrote: > Hello, > and sorry for asking a question without the data - hope it can still > be answered:
> I've run two things on the same data: > # Using lme: > mix.lme <- lme(DV ~a+b+c+d+e+f+h+i, random = random = ~ e+f+h+i| > group, data = mydata) > # Using lmer > mix.lmer <- lmer(DV > ~a+b+c+d+(1|group)+(e|group)+(f|group)+(h|group)+(i|group), data = > mydata) Those models aren't the same and the model for lmer doesn't make sense. You would need to write the random effects terms as (0+e|group), etc. because (e|group) is the same as (1 + e|group) so you are including (Intercept) random effects for group in each of those 5 terms. To generate the same model as you fit with lme you would use mix.lmer <- lmer(DV ~a+b+c+d+(e+f+g+h+ii|group), mydata) I wouldn't recommend it though as this requires estimating 21 variance and covariance parameters for the random effects. Almost certainly the estimated variance-covariance matrix will end up being singular. Unless you are careful you may not notice this. > lme provided an output (fixed effects and random effects coefficients). lme is not as picky about singularity of the variance-covariance matrix as lmer is. > lmer gave me an error: Error in mer_finalize(ans) : Downdated X'X is > not positive definite, 10. > I've rerun lmer with - but specifying the random effects for 2 fewer > predictors. This time it ran and provided an output. (BTW, the random > effects of lmer with 2 fewer predictors specified as random were very > close to the output of lme). Yes, lmer could converge in such as case but the parameter estimates are not meaningful because of the ambiguity described above. > Question: > Looks like lmer could not invert the matrix, right? Well, lmer never tries to invert matrices but it does factor them and that is where the problem is recognized. However, I think that singularity is a symptom of the problem, not the cause. > But how come lme > (which I thought was an earlier version of lmer) COULD invert it? The computational methods in the two packages are quite different. I think that the methods in lme4 are superior because we have learned a bit in the last 10 years. > Greatly appreciate a clarification! > > > -- > Dimitri Liakhovitski > Ninah Consulting > www.ninah.com > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
