Dear "R workers",
I have a question about a mixed logistic regression for
repeated data. After fitting a traditional logistic
regression a quasi-complete separation with too large SE
for a covariate (sex) was shown. In these days I read a
lot of pubblication about the possible solutions of
quasi-complete separation (such as exact logit, Firth
method, delete variable, etc.). I tried with "zelig" and
"logistf" and some improvement were seen. Now I would like
to reduce the quasi complete separation bias for mixed
logistic regression, but I don't known how to do it. Is
the Bayesian inference the best choice?
Could you help me?
Thanks in advance!
Massimo Fenati
MASSIMO FENATI
-----------------------------------------
Medico Veterinario (DVM)
Via Barchessa, 19
35040 - Boara Pisani (PD)- Italy
tel: +39 0425958083
cel: +39 3392114911
fax: +39 0425958083
e-mail: massimo.fen...@infs.it
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