[R-sig-ME] lme4 question
bbolker at gmail.com
Sat May 10 20:05:40 CEST 2014
On 14-05-08 08:34 PM, Francis, David wrote:
> I have an R/lme4 question that is vexing me, and I am hoping that you
> can provide some direction (even a hint at where I should look would
> be fine).
I thought I had answered this, but it must have slipped through the
If you look at the ?lmerControl manual page, you'll see the
check.nobs.vs.nlev (you may need check.nobs.vs.nRE as well, I don't
remember) which will allow you to override/bypass this check.
The reason for this default is that, although there _are_ use cases
(such as yours) where the unidentifiability of the variance-covariance
matrix doesn't matter, people who specify these models most often (in my
experience) don't know they are doing it, and usually don't want to.
hope that helps,
> We have been using R and lme4 to extract variance components and
> BLUPs for quality traits from field trials of tomato. There is a data
> set that I have been using for teaching purposes in my plant breeding
> class. The data set is unbalanced and has some missing data such
> that there is only 1 level for one term in the model.
> When we first started using lme4, we were using R version 2.15.0
> the model y = lmer(BRIX~ (1|LINE) + (1|LOC) + (1|YEAR) +
> (1|REP%in%LOC:YEAR) + (1|LINE:LOC) + (1|LINE:YEAR))
> was used to generate the variance components and to extract BLUPs for
> lines (different inbred lines, or varieties).
> However with newer core packages, the model leads to an error (with
> the same data set as used above...)
> Error in checkNlevels(reTrms$flist, n = n, control): grouping factors
> must have > 1 sampled level
> This error suggests that the model is over-parametrized; and if I
> drop the interaction REP%in%LOC:YEAR, I can again generate variance
> components and extract BLUPs. The variance components for the
> remaining terms are identical to those obtained using R version
> If I reload R version 2.15.0 Plus adding the following 3 work
> packages to the library; lme4_0.999902344-0.zip; minqa_1.2.1.zip;
> Rcpp_0.9.10.zip the model works and estimates are the same as when we
> first started using the data set and R in class back in 2011.
> The simple question (which probably isn't): what has changed with the
> core-package and or lme4 that the same data set is leading to an
> error in newer versions?
> Thanks for any direction that you can provide.
> David _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
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