Hi, I try to make a binomial analysis using GLMM in a longitudinal data file. Is correct to use anova(model) to access the significance of the fixed terms? Thanks Ronaldo -- Todos somos iguais perante a lei, mas nao perante os encarregados de faze-las cumprir. -- S. Jerzy Lec -- |> // | \\ [***********************************] | ( ? ? ) [Ronaldo Reis J?nior ] |> V [UFV/DBA-Entomologia ] | / \ [36571-000 Vi?osa - MG ] |> /(.''`.)\ [Fone: 31-3899-4007 ] | /(: :' :)\ [chrysopa at insecta.ufv.br ] |>/ (`. `'` ) \[ICQ#: 5692561 | LinuxUser#: 205366 ] | ( `- ) [***********************************] |>> _/ \_Powered by GNU/Debian Woody/Sarge
Ronaldo Reis-Jr. wrote:> Hi, > > I try to make a binomial analysis using GLMM in a longitudinal data file. > > Is correct to use anova(model) to access the significance of the fixed terms? > > Thanks > RonaldoFrom lme4_0.95-1 on the GLMM function has been replaced by lmer with a non-missing family argument. For the time being I would recommend staying with lme4_0.9-x and using the anova(model) from that but bear in mind that the Wald approximate tests are notoriously inaccurate for some generalized linear models and generalized linear mixed models. If you have only a single level of random effects and you also have access to SAS I would suggest cross-checking the results against those from SAS PROC NLMIXED. Getting better results for this calculation in lmer models is on my "To Do" list but there are a lot of other tasks above it.