[R-sig-ME] Problems in using lmer to fit a multilevel model

David Duffy 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
> observations.

> 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.
| 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

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