[R-sig-ME] Problems in using lmer to fit a multilevel model
Douglas Bates
bates at stat.wisc.edu
Wed Aug 20 18:19:01 CEST 2008
2008/8/20 chenlei <chenlei at ibcas.ac.cn>:
> Dear£¬
> when I fitted my logistic model(binary data),I received an error "Error in mer_finalize(ans, verbose) : q = > n = ". what's the matter?how can I do with this problem? was this tell me the observations were not enough to fit the model ? I appreciate if anyone who use lmer could give me some advice.
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?
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