[R-sig-ME] Theoric rapid doubts about glmer()
db@r@cort|n@ @end|ng |rom gm@||@com
Wed Apr 24 16:45:30 CEST 2019
My previous e-mail with links has not been slipped through the cracks. For
this reason, this second time, only I send two teoric doubts if someone
could help me to understand two simple doubts but for me (as PhD student
with a curiosity in statistics) I've not capable to solve by myself yet.
1- As general rule, in glmer models if we have only one random effect,
maybe it's more recommended always to perform a Gauss-Hermite Quadrature
approximation instead of Laplace approximation because we can perform more
than one iteration?
2 - I've read some posts addressing why the variance of Random effect
differs between lmer and glmer... ([(
Due to non-normality of my data (not attached), I need to use glmer, but
how can I explain that the variance of my random variable (Horse) is
Performing an analogous analysis by lmer (assuming badly "normality") the
variance of my random variable (Horse) increased up to 33%!!! I think that
horse, must be an important value of explaining the variance of my model
(as states lmer model).
Therefore, I perform glmer and I obtained a variance for Horse as random
effect of 0, meanwhile performing a lmer() I obtained a variance for Horse
as random effect of 33%. How can I assess the importance of the random
effect on my model? How can I interpret well the model?
Thanks on advance for your help,
University of Lleida // INRA Jouy-en-Josas
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