[R-sig-ME] Problems in using lmer to fit a multilevel model
David.Duffy at qimr.edu.au
Thu Aug 21 04:48:45 CEST 2008
On Wed, 20 Aug 2008, Douglas Bates wrote:
> 2008/8/20 chenlei <chenlei at ibcas.ac.cn>:
>> when I fitted my logistic model(binary data),
>> I received an error "Error in mer_finalize(ans, verbose) : q = > n = ".
> Hmm. The message was supposed to be a bit more informative in that it
> should have given the values of q and n. I will repair that.
> The value of q is the total number of random effects and the value of
> n is the number of observations. I included that check because it did
> not make sense to me to try to fit more random effects than you have
> I guess I could be persuaded that it would make sense
> in some circumstances because the random effects are determined by a
> penalized least squares optimization.
> What is the nature of the model that would require it to have more
> random effects than observations?
Commonly, genetic models fit 2 or more random effects per individual, with
different prespecified covariance matrices (A, D, A*A, A*D...)
| David Duffy (MBBS PhD) ,-_|\
| email: davidD at qimr.edu.au ph: INT+61+7+3362-0217 fax: -0101 / *
| Epidemiology Unit, Queensland Institute of Medical Research \_,-._/
| 300 Herston Rd, Brisbane, Queensland 4029, Australia GPG 4D0B994A v
More information about the R-sig-mixed-models