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.fenati at infs.it