Hello,
I am trying to simplify backwards a mixed effects model, using lmer
function from lme4 package. As my data are species numbers and there
exists overdisperison, I think appropriate to use glmer function with
error family quasipoisson. I compare one model with its simplification
through log-likelihood ratio tests.
Nevertheless, once I have selected a simplified model, I find in the
summary of this 'significant' model that estimated coefficients are
associated to very big standard errors, to the point that no one of
the coefficients seem to be significantly different from zero.
Here come my questions:
Can anybody explain this contradiction among standard errors of the
estimated coefficients and the significance of the model?
Is unappropriated to use Log-likelihood backwards simplification with
quasipoisson errors?
Thank you in advance!
--
Albert Romero Puente
Departament de Biologia Vegetal-Botànica
Universitat de Barcelona
Facultat de Biologia
3a Planta
Av. Diagonal, 645. (08028) Barcelona
Tel. 0034 93 402 14 71
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