random slopes and intercepts using glmmadmb - negative binomial
Bayes Student <bayes.student at ...> writes:
Hello, I am new to mixed modeling and using the glmmadmb package. I am interested in using glmmadmb to model count data with a negative binomial distribution, using year and site sampled as my random effect variables, as both should be allowed to vary independently. I would like to consider random intercepts for both factors, but also random slopes for sites across all years. I am not sure how to code this in R, and have tried several different ways. Usually R just takes a super long time and does not seem to complete the computation - which leads me to think my syntax is incorrect. Any suggestions/ thoughts would be greatly appreciated! I'm using Windows 7 with RStudio v.0.98.312.
The version of R and glmmADMB are more relevant than the version of RStudio, for what it's worth.
Here is what works - random intercepts model:
mod <- glmmadmb(species~(1|year)+(1|site),data=cs,
family="nbinom2",link="log")
Here are some iterations I have tried which did not seem to work:
mod <- glmmadmb(species~(1+site|year)+(1|site),data=cs,...)
mod <- glmmadmb(species~(site|year)+(1|site),data=cs,...)
mod <- glmmadmb(species~(1|year)+(1|site)+(0|site),data=cs,...)
[snip] I think you're looking for species ~ year + (1|year) + (year|site) , equivalent to species ~ year + (1|year) + (1+year|site) In the syntax (A|B), B is the *grouping variable* and A represents the factor or factors that vary among groups. The slight oddity of this model is that year appears three times, once as a main effect (the overall log-linear effect of year), once as a grouping variable (the year-by-year variation across all sites around the log-linear trend) and once as a random effect (the random variation of log-linear trend among sites).